Enhanced hotel recommendation method addressing the deviation between overall rating and detailed criteria ratings on Tripadvisor.com

2021 ◽  
pp. 1-16
Author(s):  
Leiguang Zhong ◽  
Yiyue Luo ◽  
Xin Zhang ◽  
Hongyu Zhang ◽  
Jianqiang Wang
Keyword(s):  
Decision Making ◽  
Service Providers ◽  
Recommendation Systems ◽  
Actual Data ◽  
Proposed Model ◽  
Hotel Service ◽  
Rating Information ◽  
Comprehensive Score

User rating information on multiple predefined aspects gathered by hotel recommendation systems generally shows a deviation between the overall rating and detailed criteria ratings. In this study, to address this deviation, we proposed a novel hotel recommendation method that clusters users with different preferences into different groups using the K-means algorithm. Moreover, we allocated weights to different criteria and obtained a comprehensive score. A case study on actual data from Tripadvisor.com showed that compared with three other models, our proposed model demonstrated a more impressive performance. This research can offer advantages to hotel service providers and customers in terms of decision making.

Learning from failures: Design improvements using a multiple criteria decision-making process

2003 ◽  
Vol 217 (4) ◽  
pp. 207-216 ◽  
Author(s):  
G G Davidson ◽  
A W Labib
Keyword(s):  
Decision Making ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Mathematical Representation ◽  
Analytic Hierarchy ◽  
Proposed Model ◽  
Invaluable Tool ◽  
History Of

This paper proposes a new concept of decision analysis based on a multiple criteria decision making (MCDM) process. This is achieved through the provision of a systematic and generic methodology for the implementation of design improvements based on experience of past failures. This is illustrated in the form of a case study identifying the changes made to Concorde after the 2000 accident. The proposed model uses the analytic hierarchy process (AHP) mathematical model as a backbone and integrates elements of a modified failure modes and effects analysis (FMEA). The AHP has proven to be an invaluable tool for decision support since it allows a fully documented and transparent decision to be made with full accountability. In addition, it facilitates the task of justifying improvement decisions. The paper is divided as follows: the first section presents an outline of the background to the Concorde accident and its history of related (non-catastrophic) malfunctions. The AHP methodology and its mathematical representation are then presented with the integrated FMEA applied to the Concorde accident. The case study arrives at the same conclusion as engineers working on Concorde after the accident: that the aircraft may fly again if the lining of the fuel tanks are modified.

A Hybrid Heuristic for QoS Aware Matching of User's Job and Virtual Machines in Cloud Environment

2018 ◽  
Vol 11 (2) ◽  
pp. 88-109
Author(s):  
Devki Nandan Jha ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Virtual Machines ◽  
Service Providers ◽  
Cloud Provider ◽  
Technological Advancement ◽  
Cloud Platform ◽  
Analytical Hierarchical Process ◽  
Hybrid Heuristic ◽  
Proposed Model

Cloud computing is a technological advancement that provides services in the form of utility on a pay-per-use basis. As the cloud market is expanding, numerous service providers are joining the cloud platform with their services. This creates an indecision amongst the users to choose an appropriate service provider especially when the cloud provider provisions diverse type of virtual machines. The problem becomes more challenging when the user has different jobs requiring specific quality of service. To address the aforementioned problem, this article applies a hybrid heuristic using College Admission Problem and Analytical Hierarchical Process for stable matching of the users' job with the cloud's virtual machines. The case study depicts the effectiveness of the proposed model.

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.

scholarly journals A fuzzy-TOPSIS model for maintenance outsourcing considering the quality of submitted tender documents

2021 ◽  
Vol 23 (3) ◽  
pp. 443-453
Author(s):  
Maysa Alshraideh ◽  
Shereen Ababneh ◽  
Elif Elcin Gunay ◽  
Omar Al-Araidah
Keyword(s):  
Decision Making ◽  
Selection Criteria ◽  
Fuzzy Topsis ◽  
Final Decision ◽  
Proposed Model ◽  
Maintenance Outsourcing ◽  
Multiple Experts ◽  
Decision Making Model

The paper provides a multiple-experts Fuzzy-TOPSIS decision-making model for the selection among maintenance contractors based on the quality of tendering documents. The study introduces a set of selection criteria utilizing benefit and cost criteria from literature. The proposed model aggregates subjective linguistic assessments of multiple experts that express their opinions on the degree of importance of criteria and allows multiple decisionmakers to evaluate the compliance of contractors’ documents. For a case study, the model is applied to select among contractors tendering to maintain the heavy-duty cranes of an international steel company from literature. Several decision-making scenarios are investigated, and major changes in the final decision are observed. The changes in obtained results illustrate the need to better address uncertainties in rating and tendering an overqualified contractor at a higher cost.

A novel model for risk management of outsourced construction projects using decision-making methods: a case study

2020 ◽  
Vol 10 (2) ◽  
pp. 97-123 ◽  
Author(s):  
Amin Mahmoudi ◽  
Mehdi Abbasi ◽  
Xiaopeng Deng ◽  
Muhammad Ikram ◽  
Salman Yeganeh
Keyword(s):  
Decision Making ◽  
Construction Projects ◽  
Project Managers ◽  
Analytic Hierarchy ◽  
Suitable Alternative ◽  
Content Type ◽  
Proposed Model ◽  
The Cost ◽  
First Time

PurposeSelecting a suitable contract to outsource construction projects is an ongoing concern for project managers and organizational directors. This study aims to propose a comprehensive model to manage the risks of outsourced construction project contracts.Design/methodology/approachTo employ the proposed model, firstly, the types of contracts and risks in the organization should be identified, then, to prioritize the contracts, the identified risks are considered as criteria. After receiving the experts' opinions, the best–worst method (BWM) integrated with grey relation analysis (GRA) method was used to prioritize the contracts. BWM and GRA are multi-criteria decision-making methods with different approaches and applications. In the current study, BWM has been employed to calculate the weights of criteria because it has better performance than other methods such as the analytic hierarchy process (AHP). After calculating the weights of criteria, the GRA method has been utilized for ranking the alternatives.FindingsAccording to the results obtained from the case study, the cost plus award fee contract is the most suitable alternative for outsourcing construction projects. The proposed methodology can be practically applied through different types of the projects such as construction or “engineering, procurement and construction”.Originality/valueTo the best of our knowledge, this is the first time a conceptual model has been proposed to select an appropriate contract for construction projects. Also, for the first time, the BWM integrated with GRA method has been used to prioritize project contracts based on the potential risks. The proposed model can contribute to project managers for selecting a suitable contract with the least risk in construction projects.

Designing differential service strategy for two-dimensional warranty based on warranty claim data under consumer-side modularisation

2019 ◽  
Vol 234 (3) ◽  
pp. 550-561
Author(s):  
Tong Peng ◽  
Liu Chunling
Keyword(s):  
Service Providers ◽  
Claim Data ◽  
Two Dimensional ◽  
Function Type ◽  
Service Strategy ◽  
Actual Usage ◽  
Proposed Model ◽  
Warranty Service ◽  
The Mathematical Model

With the development of modular manufacturing technology and diversified demand for products, the demand for differential warranty service has become increasingly prominent. This article proposes a differential service strategy for two-dimensional warranty using warranty claim data under consumer-side modularisation. In contrast to previous research that optimised maintenance strategies under a given failure density function, this article obtains actual usage rate and failure density functions of main failure types by determining the function type and parameter fitting. A detailed case study of a product under a two-dimensional warranty is discussed to interpret the proposed model. Using the mathematical model proposed in this research, warranty service providers can offer consumers a differential warranty service under consumer-side modularisation.

Strategic Decision Making for Outsourcing Information Systems with a Fuzzy Multi-criteria Decision-Making Approach

2018 ◽  
Vol 6 (8) ◽  
pp. 6
Author(s):  
Mahmoud Modiri ◽  
Mohammad Dashti
Keyword(s):  
Decision Making ◽  
Analytic Network Process ◽  
Decision Makers ◽  
Strategic Decision ◽  
Multi Criteria Decision Making ◽  
Service Support ◽  
Proposed Model ◽  
Network Process ◽  
Selection Of

Today, IS supplier selection is one of the most critical steps in the outsourcing process; the success of outsourcing is highly dependent on the selection of IS suppliers. This paper proposes a new hybrid fuzzy multi-criteria decision-making (MCDM) model, which uses decision-making trial and evaluation laboratory (DEMATEL) technique, analytic network process (ANP), and Vlse Kriterijumska Optimizacija I Kompromisno Resenje(VIKOR) to evaluate four potential suppliers using seven factors and five decision makers using a realistic case study. the results showed that Service support is importance for outsourcing. The proposed model can help practitioners improve their decision making process.

scholarly journals Decision-Making Tool for Enhancing the Sustainable Management of Cultural Institutions: Season Content Programming at Palau De La Música Catalana

2020 ◽  
Vol 12 (14) ◽  
pp. 5785
Author(s):  
Maria del Mar Casanovas-Rubio ◽  
Carolina Christen ◽  
Luz María Valarezo ◽  
Jaume Bofill ◽  
Nela Filimon ◽  
...  
Keyword(s):  
Decision Making ◽  
Sustainable Management ◽  
Qualitative Interviews ◽  
Real Data ◽  
Cultural Institutions ◽  
Cultural Institution ◽  
Proposed Model ◽  
Complex Decision ◽  
Cultural Sector

There has been an increasing relevance of the cultural sector in the economic and social development of different countries. However, this sector continues without much input from multi-criteria decision-making (MDCM) techniques and sustainability analysis, which are widely used in other sectors. This paper proposes an MCDM model to assess the sustainability of a musical institution’s program. To define the parameters of the proposed model, qualitative interviews with relevant representatives of Catalan cultural institutions and highly recognized professionals in the sector were performed. The content of the 2015–2016 season of the ‘Palau de la Música Catalana’, a relevant Catalan musical institution located in Barcelona, was used as a case study to empirically test the method. The method allows the calculation of a season value index (SVI), which serves to make more sustainable decisions on musical season programs according to the established criteria. The sensitivity analysis carried out for different scenarios shows the robustness of the method. The research suggests that more complex decision settings, such as MCDM methods that are widely used in other sectors, can be easily applied to the sustainable management of any type of cultural institution. To the best of the authors’ knowledge, this method was never applied to a cultural institution and with real data.

Midstream social marketing and the co-creation of public services

2016 ◽  
Vol 6 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Matthew Wood
Keyword(s):  
Social Networks ◽  
Social Marketing ◽  
Public Services ◽  
Service Providers ◽  
Content Type ◽  
Proposed Model ◽  
Service Staff ◽  
Client Relationships

Purpose This paper aims to highlight the importance of social marketing at the midstream (meso) level as a key component of a proposed model for co-creating public services. The model demonstrates how supportive relationships and conversations within and between service organisations, front-line service staff, social networks and clients are essential for the effective co-creation of health and welfare services and social marketing interventions. Design/methodology/approach This is a conceptual paper that uses network and services theory and a case study to show how the midstream social marketing approach and service co-creation can be applied in practice and how these concepts relate to upstream and downstream social marketing. Findings The case study demonstrates the powerful role of social networks, staff–client relationships and conversations in the co-creation of effective services and the improvement in communications, trust and understanding between service providers and the community. Practical implications The paper shows how service providers and social marketers can achieve co-created, customer-oriented services/interventions through the development of congruent, empathetic narratives, relationships and conversations. The case study demonstrates how this can be achieved in practice through staff training, the identification of “community communicators” and value-based targeting and communications. Originality/value The integration of conversations, relationships, values, services and midstream social marketing into a model for co-creation offers a valuable tool for social marketing and health/welfare service professionals.

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