scholarly journals Tactical runway scheduling for demand and delay management

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Álvaro Rodríguez-Sanz ◽  
Rosa Maria M. Arnaldo Valdes ◽  
Javier A. Pérez-Castán ◽  
Pablo López Cózar ◽  
Victor Fernando Gómez Comendador
Keyword(s):  
Decision Making ◽  
Service Providers ◽  
System Capacity ◽  
Main Element ◽  
Programming Approach ◽  
Planning Problem ◽  
Delay Management ◽  
Efficient Operation ◽  
Content Type ◽  
Runway Scheduling

Purpose Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and determined operational requirements. In such a constrained operating environment, any reduction in system capacity results in major delays with significant costs for airlines and passengers. Therefore, the efficient operation of airports is a critical cornerstone for demand and delay management of the whole air transportation system. Runway scheduling deals with the sequencing of arriving and departing aircraft at airports such that a predefined objective is optimized subject to several operational constraints, like the dependency of separation on the leading and trailing aircraft type or the runway occupancy time. This study aims to develop a model that acts as a tactical runway scheduling methodology for reducing delays while managing runway usage. Design/methodology/approach By considering real airport performance data with scheduled and actual movements, as well as arrival/departure delays, this study presents a robust model together with an optimization algorithm, which incorporates the knowledge of uncertainty into the tactical operational step. The approach transforms the planning problem into an assignment problem with side constraints. The coupled landing/take-off problem is solved to optimality by exploiting a time-indexed (0, 1) formulation for the problem. The Binary Integer Linear Programming approach allows to include multi-criteria and multi-constraints levels and, even with some major simplifications, provides fewer sequence changes and target time updates, when compared to the usual approach in which the plan is simply updated in case of infeasibility. Thus, the use of robust optimization leads to a protection against tactical uncertainties, reduces delays and achieves more stable operations. Findings This model has been validated with real data from a large international European airport in different traffic scenarios. Results are compared to the actual sequencing of flights and show that the algorithm can significantly contribute to the reduction of delay, while adhering as much as possible to the operative procedures and constraints, and to the objectives of the airport stakeholders. Computational experiments performed on the case study illustrate the benefits of this arrival/departure integrated approach: the proposed algorithm significantly reduces weighted aircraft delay and computes efficient runway schedule solutions within a few seconds and with little computational effort. It can be adopted as a decision-making tool in the tactical stage. Furthermore, this study presents operational insights regarding demand and delay management based on the results of this work. Originality/value Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations among involved flights. In the context of the Airport Collaborative Decision Making programme, airport operators and air navigation service providers require arrival and departure management tools that improve aircraft flows at airports. Airport runway optimization, as the main element that combines airside and groundside operations, is an ongoing challenge for air traffic management.

scholarly journals A comparison of high-speed internet service in Ghana: an analytical hierarchy approach

2018 ◽  
Vol 31 (1) ◽  
pp. 181-198 ◽  
Author(s):  
Michael F. Frimpon ◽  
Ebenezer Adaku
Keyword(s):  
Decision Making ◽  
High Speed ◽  
Service Providers ◽  
Analytical Techniques ◽  
Analytical Framework ◽  
Sub Saharan Africa ◽  
Performance Criteria ◽  
Internet Service ◽  
Content Type ◽  
Sub Saharan

Purpose The rising proportion of internet users in Sub-Saharan Africa and the lack of analytical techniques, as decision support systems, in choosing among alternative internet service providers (ISPs) by consumers underpin this study. The purpose of this paper is to propose an approach for evaluating high-speed internet service offered by ISPs in a sub-Saharan African country. Design/methodology/approach Using a sample size of 150, pairwise comparisons of two ISPs along five criteria of cost, usability, support, reliability and speed were performed by ten person groups of university students working in various organizations in Ghana and undertaking an online Six Sigma Course. Geometric means were employed to aggregate the scores in 15 groups, and these scores were then normalized and used as input into an analytical hierarchy process grid. Findings The results show that consumers of internet services highly emphasize the cost attribute of internet provision in their decision making. On the other hand, it was realized that consumers least emphasize the support provided by ISPs in their decision making among alternative ISPs. Originality/value This study has sought to provide an analytical framework for assessing the quality of service provided by alternative ISPs in a developing economy’s context. The evaluating criteria in this framework also reveal the key consumer requirements in internet service provision in a developing economy’s environment. This, to a large extent, will inform the marketing strategies of existing ISPs in Ghana as well as prospective ones intending to enter the Ghanaian market. Besides, the National Communication Authority, a regulator of communication services provision in Ghana, will be informed about the performances of the ISPs along five performance criteria. This is expected to aid in their regulatory functions.

Consumer empowerment in insurance

2018 ◽  
Vol 36 (6) ◽  
pp. 1073-1097 ◽  
Author(s):  
Pascal Buehler ◽  
Peter Maas
Keyword(s):  
Decision Making ◽  
Self Efficacy ◽  
Service Providers ◽  
Time Lag ◽  
Decision Making Process ◽  
Consumer Empowerment ◽  
Content Type ◽  
Perceived Performance ◽  
Performance Risk ◽  
The Impact

Purpose The purpose of this paper is to enhance the understanding of consumer empowerment in the relationship between consumers and service providers. It draws on self-efficacy theory to conceptualize consumer empowerment and explain the impact on perceived performance risk in insurance decision making. Design/methodology/approach This study employs data collected from an online survey involving 487 consumers in Switzerland, who recently decided on an insurance service. A structural equation model quantifies both the psychological effects on consumers’ perception of insurance services and behavioral effects on their decision-making process. Findings Perceived consumer empowerment is conceptualized by perceived self-efficacy and perceived controllability. Both have a significant impact on perceived performance risk, while the former is partially mediated by the preference to delegate the decision to a surrogate. Moreover, customers’ involvement in the purchase process moderates both the direct and indirect effect of perceived self-efficacy on perceived performance risk. Research limitations/implications The results are based on consumers’ perceptions from a single country. Furthermore, consumers’ perceptions were surveyed with a time lag after the decision-making process. To increase rigor, perceptions should be collected during decision making. Practical implications Results show that consumer empowerment can be employed as a risk reduction strategy. Consumers with self-efficacy and controllability beliefs perceive significantly less performance risk; however, practitioners should consider that consumers are also motivated to make decisions independently rather than delegating their decisions. Furthermore, consumer empowerment depends on consumer will. For largely indifferent consumers, empowerment does not affect risk or decision delegation preference. Originality/value The study is among the few empirical works to examine the effects of consumer empowerment on the consumer-service provider relationship on an individual level. Furthermore, applying consumer empowerment in relationship marketing implies a shift in research focus to the question of how consumers construe decision-making situations rather than objectively measuring the state of consumer relationship.

IoT-based real time intelligent routing for emergent crowd evacuation

2019 ◽  
Vol 37 (3) ◽  
pp. 604-624
Author(s):  
Yanlan Mei ◽  
Ping Gui ◽  
Xianfeng Luo ◽  
Benbu Liang ◽  
Liuliu Fu ◽  
...  
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Programming Model ◽  
Emergency Evacuation ◽  
Guidance System ◽  
Programming Approach ◽  
Metro Station ◽  
Content Type ◽  
Crowd Evacuation ◽  
Evacuation Route

Purpose The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station. Design/methodology/approach The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced. Findings The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation. Originality/value The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

Implementation of 3D printing and the effect on decision making in logistics management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stefan Hecker
Keyword(s):  
Decision Making ◽  
3D Printing ◽  
Service Providers ◽  
Logistics Management ◽  
Service Development ◽  
Content Type ◽  
Disruptive Technologies ◽  
Logistics Service ◽  
Service Portfolio ◽  
The Impact

PurposeFrom a synthesis of literature, the purpose of this paper is to present a conceptual service development methodology showing the impact of 3D printing as a disruptive technology to the service portfolio. The methodology is designed to support practitioners and academics in better understanding the impact of disruptive technologies may have to the service portfolio and participate in the technology.Design/methodology/approachA literature review is conducted and based on these findings a conceptual framework has been developed.FindingsThe design of a methodology for the development of 3D printing services is used to evaluate the disruption potential of 3D printing and to implement the technology in the service portfolio of a logistics service provider. The disruption potential of 3D printing influences a logistics manager by make to order decisions. In addition, it could be proven the service portfolio was diversified.Research limitations/implicationsLiterature directly dealing with technology-based service development for decision making in logistics management is rare and thus the methodology is built on insights, compiled from the distinct research areas. Further research should be performed on this nascent topic.Practical implicationsLogistics service providers may use the developed methodology to revise their service portfolio by the consideration of disruptive technologies, in order to reduce strategic misdecisions regarding the range of services.Originality/valueThis paper looks specifically at decision making for implementing disruptive technologies to the service portfolio.

Modelling near-real-time order arrival demand in e-commerce context: a machine learning predictive methodology

2020 ◽  
Vol 120 (6) ◽  
pp. 1149-1174 ◽  
Author(s):  
K.H. Leung ◽  
Daniel Y. Mo ◽  
G.T.S. Ho ◽  
C.H. Wu ◽  
G.Q. Huang
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Real Time ◽  
Service Providers ◽  
Series Data ◽  
Illustrative Case ◽  
Implementation Framework ◽  
Inference System ◽  
Content Type

PurposeAccurate prediction of order demand across omni-channel supply chains improves the management's decision-making ability at strategic, tactical and operational levels. The paper aims to develop a predictive methodology for forecasting near-real-time e-commerce order arrivals in distribution centres, allowing third-party logistics service providers to manage the hour-to-hour fast-changing arrival rates of e-commerce orders better.Design/methodology/approachThe paper proposes a novel machine learning predictive methodology through the integration of the time series data characteristics into the development of an adaptive neuro-fuzzy inference system. A four-stage implementation framework is developed for enabling practitioners to apply the proposed model.FindingsA structured model evaluation framework is constructed for cross-validation of model performance. With the aid of an illustrative case study, forecasting evaluation reveals a high level of accuracy of the proposed machine learning approach in forecasting the arrivals of real e-commerce orders in three different retailers at three-hour intervals.Research limitations/implicationsResults from the case study suggest that real-time prediction of individual retailer's e-order arrival is crucial in order to maximize the value of e-order arrival prediction for daily operational decision-making.Originality/valueEarlier researchers examined supply chain demand, forecasting problem in a broader scope, particularly in dealing with the bullwhip effect. Prediction of real-time, hourly based order arrivals has been lacking. The paper fills this research gap by presenting a novel data-driven predictive methodology.

Spatial usage analysis based on user activity big data logs in library

2019 ◽  
Vol 38 (3) ◽  
pp. 678-698 ◽  
Author(s):  
Tae-Young Kim ◽  
Ju-Yeon Gang ◽  
Hyo-Jung Oh
Keyword(s):  
Decision Making ◽  
Public Library ◽  
Time Of Day ◽  
National Library ◽  
Efficient Operation ◽  
Content Type ◽  
Usage Rate ◽  
Depth Analysis ◽  
Spatial Usage ◽  
Support Decision Making

Purpose This study explored spatial usage of a public library based on activity logs produced by real users. The purpose of this paper is to provide preliminary data for decision-making when establishing the library operation policy. Design/methodology/approach To achieve the goal, the author collected a variety of data including 274,242 seat reservations logs, 3,361,284 collection usage logs, and 96,098 user information for the four years in which the National Library of Korea, Sejong actually operated. The crawled data were analyzed statistically in terms of demography, month, day of week, time of day and room by room. The author conducted additional in-depth analysis according to the external factors such as weather or social demographic environment. Finally, the author discussed several issues and verified feasibility of the proposals to support decision-making in operating a library in conclusion with a secondary librarian interview. Findings The usage rate in all the spaces of the National Library of Korea, Sejong, has been increasing since its opening, and, in particular, the usage rate increases sharply in January, February, July and August. In addition, the usage rate during weekends was higher than that during weekdays, and all the four spaces had a high usage rate during the afternoon. These results seem to be related to weather, users’ life pattern, users’ age, and position of PCs and seats. Based on the circulation logs analysis of children’s collections, users in their 10s and 40s showed the same space usage pattern. Originality/value This study has significance in that it attempted to analyze logs produced by real users during the actual library operation period, which has not been frequently attempted in the previous studies on libraries. The findings will be provided as basic data to support decision-making for efficient operation of libraries.

Environmentally responsible freight transport service providers' assessment under data-driven information uncertainty

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aalok Kumar ◽  
Ramesh Anbanandam
Keyword(s):  
Decision Making ◽  
Emerging Economies ◽  
Service Providers ◽  
Freight Transportation ◽  
Freight Transport ◽  
Data Driven ◽  
Transport Service ◽  
Content Type ◽  
Environmentally Responsible ◽  
Transport Industry

PurposeFreight transportation practices accounted for a significant share of environmental degradation and climate change over the years. Therefore, environmentally responsible transport practices (ERTPs) become a serious concern of freight shippers and transport service providers. Past studies generally ignored the assessment of ERTPs of freight transport companies during a transport service contract. To bridge the above literature gap, this paper proposed a hierarchical framework for evaluating freight transport companies based on ERTPs.Design/methodology/approachIn a data-driven decision-making environment, transport firm selection is affected by multiple expert inputs, lack of information availability, decision-making ambiguity and background of experts. The evaluation of such decisions requires a multi-criteria decision-making method under a group decision-making approach. This paper used a data-driven method based on the intuitionistic fuzzy-set-based analytic hierarchy process (IF-AHP) and VIseKriterijumska Kompromisno Rangiranje (IF-VIKOR) method. The applicability of the proposed framework is validated with the Indian freight transport industry.FindingsThe result analysis shows that environmental knowledge sharing among freight transport actors, quality of organizations human resource, collaborative green awareness training programs, promoting environmental awareness program for employees and compliance of government transport emission law and practice have been ranked top five ERTPs which significantly contribute to the environmental sustainability of freight transport industry. The proposed framework also ranked freight transport companies based on ERTPs.Research limitations/implicationsThis research is expected to provide a reference to develop ERTPs in the emerging economies freight transport industry and contribute to the development of a sustainable freight transport system.Originality/valueThis study assesses the environmental responsibility of the freight transportation industry. The emerging economies logistics planners can use proposed framework for assessing the performance of freight transportation companies based on ERTPs.

A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liudmila Ivanovna Khoruzhy ◽  
Roman Petrovich Bulyga ◽  
Olga Yuryevna Voronkova ◽  
Lidia Vladimirovna Vasyutkina ◽  
Natalya Ryafikovna Saenko ◽  
...  
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Trust Management ◽  
Service Providers ◽  
Cloud Services ◽  
Security And Privacy ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Wide Range ◽  
Industrial Cloud

PurposeNowadays, cloud platforms are used in many fields, including e-commerce, web applications, data storage, healthcare, gaming, mobile social networks, etc. However, security and privacy are still two significant concerns in this area. The target of this paper is to present a system for trust management in industrial cloud computing using the multi-criteria decision making (MCDM) approach. MCDM techniques have been developed to accommodate a wide range of applications. As a result, hundreds of approaches have been generated with even minor variations on current approaches spawning new study fields.Design/methodology/approachCloud computing provides a fully scalable, accessible and flexible computing platform for various applications. Due to the multiple applications that cloud computing has found in numerous life features, users and providers have considered providing security in cloud communications. Due to its distributive nature, dynamic space and lack of transparency in performing cloud computing, it faces many challenges in providing security. For security improvement, trust management can play a very influential role. This paper proposes a generic analytical methodology that uses a series of assessment criteria to evaluate current trust management testing prototypes in industrial cloud computing and related fields. The authors utilize a MCDM approach in the present article. Due to the multi-dimensionality of the sustainability objective and the complexities of socio-economic and biophysical processes, MCDM approaches have become progressively common in decision-making for sustainable energy.FindingsThe results of comparing and evaluating the performance of this model show its ability to manage trust and the ability to adapt to changes in the behavior of service providers quickly. Using a simulation, all results are confirmed. The results of simulations and evaluation of the present paper indicate that the proposed model provides a more accurate evaluation of the credibility of cloud service providers than other models.Practical implicationsThe number of cloud services and customers is vast and extremely competitive in cloud environments, where novel cloud services and customers can join at any time, while others can withdraw whenever they want. Because of cloud services' highly dynamic and dispersed design, trust management mechanisms must be highly flexible to obtain feedback and update trust outcomes as quickly as possible. The model presented in this article tries to improve users' trust in the cloud industry.Originality/valueUsing a method (MCDM) to find the best trust management solution based on user experience in industrial cloud computing is the novelty of this paper.

Consumers’ decision-making self-efficacy for service purchases: construct conceptualization and scale

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dena Hale ◽  
Ramendra Thakur ◽  
John Riggs ◽  
Suzanne Altobello
Keyword(s):  
Decision Making ◽  
Self Efficacy ◽  
Design Methodology ◽  
Service Providers ◽  
Reliability And Validity ◽  
Order Structure ◽  
Content Type ◽  
Study Approach ◽  
Order Construct ◽  
Scale Measure

Purpose The purpose of this study is to develop and validate a scale to determine the consumer’s level of decision-making self-efficacy for a high-involved service purchase, specifically the purchase of medical insurance. One question to ask is how service providers can help consumers purchase the services that best meet their needs? Before interventions can occur, it is necessary to benchmark consumers’ perceptions of their own decision-making control and abilities. Design/methodology/approach A scale that measures consumers’ service decision-making self-efficacy was developed using the principles established for scale development validation. A four-study approach was used to reach the research objective. Findings The research consisted of four studies designed to: generate items to measure consumer service decision-making self-efficacy (CSDMSE); purify the scale and assess its dimensionality (second-order structure); establish the reliability and validity of the scale; and establish norms to provide details on its usefulness for aiding consumers with service purchases. The scale was found to be a higher-order construct, comprising three lower-order constructs. Originality/value Research suggests that consumer self-efficacy may affect their decision-making. The greater the consumer’s self-efficacy for decision-making tasks, the more efficient the decision-making process strategies are expected to be. This is the purpose for which the CSDMSE scale measure was created: to understand how, where and when service professionals can assist consumers with making appropriate service-related decisions and purchases.

Cost efficiency of SDN-enabled service function chaining

Info ◽  
2016 ◽  
Vol 18 (5) ◽  
pp. 45-55 ◽  
Author(s):  
Nan Zhang ◽  
Heikki Hämmäinen ◽  
Hannu Flinck
Keyword(s):  
Cost Efficiency ◽  
Service Providers ◽  
Cost Savings ◽  
Mobile Network ◽  
Baseline Scenario ◽  
Lte Networks ◽  
Efficient Operation ◽  
Content Type ◽  
Service Function ◽  
The Cost

Purpose This paper models the cost efficiency of service function chaining (SFC) in software-defined LTE networks and compares it with traditional LTE networks. Design/methodology/approach Both the capital expenditure (CAPEX) and operational expenditure (OPEX) of the SFC are quantified using an average Finnish mobile network in 2015 as a reference. The modeling inputs are gathered through semi-structured interviews with Finnish mobile network operators (MNO) and network infrastructure vendors operating in the Finnish market. Findings The modeling shows that software-defined networking (SDN) can reduce SFC-related CAPEX and OPEX significantly for an average Finnish MNO in 2015. The analysis on different types of MNOs implies that a MNO without deep packet inspection sees the biggest cost savings compared to other MNO types. Practical implications Service function investments typically amount to 5-20 per cent of the overall MNO network investments, and savings in SFC may impact highly on the cost structure of a MNO. In addition, SFC acts as both a business interface, which connects the local MNOs with global internet service providers, and as a technical interface, where the 3GPP and IETF standards meet. Thus, the cost efficient operation of SFC may bring competitive advantages to the MNO. Originality/value The results show solid basis of network-related cost savings in SFC and contributes to MNOs making cost conscious investment decisions. In addition, the results act as a baseline scenario for further studies that combine SDN with virtualization to re-optimize network service functions.

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