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Article
Publication date: 29 April 2021

Mohamed Haddache, Allel Hadjali and Hamid Azzoune

The study of the skyline queries has received considerable attention from several database researchers since the end of 2000's. Skyline queries are an appropriate tool…

Abstract

Purpose

The study of the skyline queries has received considerable attention from several database researchers since the end of 2000's. Skyline queries are an appropriate tool that can help users to make intelligent decisions in the presence of multidimensional data when different, and often contradictory criteria are to be taken into account. Based on the concept of Pareto dominance, the skyline process extracts the most interesting (not dominated in the sense of Pareto) objects from a set of data. Skyline computation methods often lead to a set with a large size which is less informative for the end users and not easy to be exploited. The purpose of this paper is to tackle this problem, known as the large size skyline problem, and propose a solution to deal with it by applying an appropriate refining process.

Design/methodology/approach

The problem of the skyline refinement is formalized in the fuzzy formal concept analysis setting. Then, an ideal fuzzy formal concept is computed in the sense of some particular defined criteria. By leveraging the elements of this ideal concept, one can reduce the size of the computed Skyline.

Findings

An appropriate and rational solution is discussed for the problem of interest. Then, a tool, named SkyRef, is developed. Rich experiments are done using this tool on both synthetic and real datasets.

Research limitations/implications

The authors have conducted experiments on synthetic and some real datasets to show the effectiveness of the proposed approaches. However, thorough experiments on large-scale real datasets are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria.

Practical implications

The tool developed SkyRef can have many domains applications that require decision-making, personalized recommendation and where the size of skyline has to be reduced. In particular, SkyRef can be used in several real-world applications such as economic, security, medicine and services.

Social implications

This work can be expected in all domains that require decision-making like hotel finder, restaurant recommender, recruitment of candidates, etc.

Originality/value

This study mixes two research fields artificial intelligence (i.e. formal concept analysis) and databases (i.e. skyline queries). The key elements of the solution proposed for the skyline refinement problem are borrowed from the fuzzy formal concept analysis which makes it clearer and rational, semantically speaking. On the other hand, this study opens the door for using the formal concept analysis and its extensions in solving other issues related to skyline queries, such as relaxation.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 20 December 2018

Sanjay Jharkharia and Chiranjit Das

The purpose of this paper is to provide an analytical model for low carbon supplier development. This study is focused on the level of investment and collaboration…

Abstract

Purpose

The purpose of this paper is to provide an analytical model for low carbon supplier development. This study is focused on the level of investment and collaboration decisions pertaining to emission reduction.

Design/methodology/approach

The authors’ model includes a fuzzy c-means (FCM) clustering algorithm and a fuzzy formal concept analysis. First, a set of suppliers were classified according to their carbon performances through the FCM clustering algorithm. Then, the fuzzy formal concepts were derived from a set of fuzzy formal contexts through an intersection-based method. These fuzzy formal concepts provide the relative level of investments and collaboration decisions for each identified supplier cluster. A case from the Indian renewable energy sector was used for illustration of the proposed analytical model.

Findings

The proposed model and case illustration may help manufacturing firms to collaborate with their suppliers for improving their carbon performances.

Research limitations/implications

The study contributes to the low carbon supply chain management literature by identifying the decision criteria of investments toward low carbon supplier development. It also provides an analytical model of collaboration for low carbon supplier development. Though the purpose of the study is to illustrate the proposed analytical model, it would have been better if the model was empirically validated.

Originality/value

Though the earlier studies on green supplier development program evaluation have considered a set of criteria to decide whether or not to invest on suppliers, these are silent on the relative level of investment required for a given set of suppliers. This study aims to fulfill this gap by providing an analytical model that will help a manufacturing firm to invest and collaborate with its suppliers for improving their carbon performance.

Details

Benchmarking: An International Journal, vol. 26 no. 1
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 7 January 2014

David Philip McArthur, Sylvia Encheva and Inge Thorsen

The aim of the paper is to propose a methodology that allows researchers and practitioners to structure a small amount of data in a way which aids understandings and…

Abstract

Purpose

The aim of the paper is to propose a methodology that allows researchers and practitioners to structure a small amount of data in a way which aids understandings and allows predictions to be made.

Design/methodology/approach

The paper explores how formal concept analysis can be combined with fuzzy reasoning to make predictions based on small datasets. A dataset of nine regions in Norway described by six attributes is used. The paper focuses on regional disparities in labour market outcomes such as unemployment and wages.

Findings

The paper finds that unemployment tends to be concentrated in the most prosperous parts of the study area. These regions have high incomes and experience population growth. More rural regions have virtually no unemployment. The methodology proposed allows these patterns to be seen. The authors made predictions with an accuracy rate of over 75 per cent.

Practical implications

A common response to high unemployment in urban areas is to stimulate employment growth. The findings suggest that this will simply increase migration towards the cities. The net result will be no change in unemployment but an accelerated depopulation of more rural regions.

Originality/value

To the authors' knowledge, this is the first application of fuzzy reasoning to the topic of regional disparities. The methodology aids in the interpretation of small datasets. The methodology should be of interested to practitioners at the local level, who are interested in analysing their own region, even when limited data are available.

Details

Journal of Economic Studies, vol. 41 no. 1
Type: Research Article
ISSN: 0144-3585

Keywords

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Article
Publication date: 11 July 2019

M. Priya and Aswani Kumar Ch.

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras…

Abstract

Purpose

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is noticeably very high. With the availability of these ontologies, the needed information can be smoothly attained, but the presence of comparably varied ontologies nurtures the dispute of rework and merging of data. The assessment of the existing ontologies exposes the existence of the superfluous information; hence, ontology merging is the only solution. The existing ontology merging methods focus only on highly relevant classes and instances, whereas somewhat relevant classes and instances have been simply dropped. Those somewhat relevant classes and instances may also be useful or relevant to the given domain. In this paper, we propose a new method called hybrid semantic similarity measure (HSSM)-based ontology merging using formal concept analysis (FCA) and semantic similarity measure.

Design/methodology/approach

The HSSM categorizes the relevancy into three classes, namely highly relevant, moderate relevant and least relevant classes and instances. To achieve high efficiency in merging, HSSM performs both FCA part and the semantic similarity part.

Findings

The experimental results proved that the HSSM produced better results compared with existing algorithms in terms of similarity distance and time. An inconsistency check can also be done for the dissimilar classes and instances within an ontology. The output ontology will have set of highly relevant and moderate classes and instances as well as few least relevant classes and instances that will eventually lead to exhaustive ontology for the particular domain.

Practical implications

In this paper, a HSSM method is proposed and used to merge the academic social network ontologies; this is observed to be an extremely powerful methodology compared with other former studies. This HSSM approach can be applied for various domain ontologies and it may deliver a novel vision to the researchers.

Originality/value

The HSSM is not applied for merging the ontologies in any former studies up to the knowledge of authors.

Details

Library Hi Tech, vol. 38 no. 2
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 27 November 2019

Hossein Sayyadi Tooranloo, Pedram Azizi and Ali Sayyahpoor

Changes in economic markets have made it necessary to understand the psychology of individual investors. Conducting effective studies on the decision of investors to buy…

Abstract

Purpose

Changes in economic markets have made it necessary to understand the psychology of individual investors. Conducting effective studies on the decision of investors to buy stock in the stock market can be useful. Therefore, it is necessary to identify and prioritize the factors affecting the decision-making of investors to purchase shares of the stock exchange. The purpose of this study was to analyze causal relationships and to weight effective factors on individual investment to purchase shares of Tehran Stock Exchange.

Design/methodology/approach

The present study is applied research in the term of its purposes and a descriptive-survey one in the term of data gathering methods. The data required in this study was collected through library and field studies. The study population included 35 investment experts. In present study, multi-criteria decision-making techniques in type-2 fuzzy environments have been used to analyze the causal relationships and weighing the factors affecting individual investment in purchasing stock in the stock market.

Findings

In the study, 4 indicators and 20 sub-indicators influencing individual investors’ decision to purchase shares of Tehran Stock Exchange were selected based on the literature review in the field of investment in the stock exchange, as well as interviews with experts. Analyzing the opinions of experts showed that they have much paid attention to financial index compare to the economic, political and psychological indicators of the market in determining the priority of indicators. In analyzing sub-indicators, it was identified that Iranian investors pay special attention to economic and political developments, political news and international economic developments.

Research limitations/implications

The present study has been carried out in Iran, and therefore, is geographically limited to Iran. In thematic terms, it is limited to effective factors of individual investments in Tehran Stock Exchange. The statistical population of present study was limited to investing experts in Tehran Stock Exchange. The difference in financial, economic, social and political conditions of individuals was another limitation of present study. The main consequences of research were the explanation of causes of investors’ higher attention to financial factors than economic, political and mental factors of market in buying stocks.

Originality/value

Given the uncertainty in the market status, using multi-criteria decision-making techniques in financial analysis can help decision-makers to make better decisions. In addition, it would be possible to take into account many variables that do not have a mathematical aspect but are important in decision-making and lead to increased decision-making satisfaction. The research initially analyzed causal relationships of determinants of individual investment on stock exchange for buying stocks through a type-2 fuzzy approach.

Details

International Journal of Ethics and Systems, vol. 36 no. 1
Type: Research Article
ISSN: 2514-9369

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Article
Publication date: 25 July 2019

Tritos Laosirihongthong, Premaratne Samaranayake and Sev Nagalingam

The purpose of this paper is to propose a holistic approach for supplier evaluation and purchasing order allocation among the ranked suppliers who meet acceptable levels…

Abstract

Purpose

The purpose of this paper is to propose a holistic approach for supplier evaluation and purchasing order allocation among the ranked suppliers who meet acceptable levels of economic, environmental and social measures.

Design/methodology/approach

A mixed research method of case study and analytical approach is adopted in this research. A fuzzy analytical hierarchical process (FAHP) is applied for ranking of suppliers. Supplier ranks are validated using judgements from multiple decision makers. Purchasing order allocation among the ranked suppliers is determined using cost minimization subject to multiple criteria of economic, environmental and social conditions. A cement manufacturing case example demonstrates and validates the proposed approach.

Findings

The research shows that both economic and environmental considerations are significant when suppliers are evaluated for sustainable procurement within the best practice of supply management process. Ranking of suppliers, based on experts’ opinions, indicates varying degrees of importance for each criterion. Adoption of sustainable procurement criteria for evaluating supplier in a cement manufacturing organization is explained by three organizational theories including resource-based, institutional and dynamic capabilities theories. Preferred suppliers from FAHP method are confirmed by judgements from multiple decision-makers. The analysis reveals that purchasing order allocation is different when suppliers are evaluated based on their relative importance and overall ranking.

Research limitations/implications

Currently, individual performance measures and decision-makers are selected from a limited set. The purchasing allocation among ranked suppliers, subjected to cost minimization, incorporates environmental objective of acceptable carbon dioxide emission and social perspective of health and safety of workers, and provides a new approach for dual supplier evaluation and purchasing allocation problem in cement industry. Adopting the proposed supplier evaluation and order allocation approach in practice needs to be guided by the operational principles and an overall methodology which is appropriate for the specific industry with sustainability objectives.

Practical implications

This research enables decision-makers to incorporate sustainability analysis in the supplier evaluation as the basis for best practice with an industry-friendly holistic approach. Using organizational theories, the research re-enforces the importance of not only the energy consumption and environmental management systems of environmental dimension as driving forces/factors from Institutional theory perspective, but also pollution controls and prevention as purchasing capabilities from resource-based theory perspective. The proposed approach is expected to motivate decision-makers to consider sustainable perspectives in supplier evaluation and order allocation processes in a global supply chain and can become a benchmarking tool.

Social implications

Suppliers’ information on health and safety of their truck drivers are used in order allocation, thus emphasizing the importance of social dimension and encouraging better conditions and benchmarking for delivery drivers.

Originality/value

This paper extends the contribution to the literature by providing guidelines for managers to set strategies, benchmarks and policies within broader sustainable supply chain practices and demonstrates the applicability of the approach using a cement-manufacturing scenario in an emerging economy.

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Article
Publication date: 4 June 2018

Marcella Brito Galvão, Raíssa Corrêa de Carvalho, Lucas Ambrósio Bezerra de Oliveira and Denise Dumke de Medeiros

The purpose of this paper is to explore marketing analysis by developing a customer loyalty approach for small- and medium-sized enterprises (SMEs) in the service sector…

Abstract

Purpose

The purpose of this paper is to explore marketing analysis by developing a customer loyalty approach for small- and medium-sized enterprises (SMEs) in the service sector, based on customer relationship management (CRM) in the context of an emerging economy.

Design/methodology/approach

This study analyzes different models of CRM in the literature and defines a loyalty approach for SMEs in the service sector. It is characterized as exploratory research, with a qualitative approach. A systematic review of the literature is undertaken as the starting point for achieving the main objective of the study.

Findings

The need to develop a framework for an approach to customer loyalty for SMEs based on CRM and to make it operational.

Research limitations/implications

It is a qualitative and exploratory study, applied only to a company’s two main clients.

Practical implications

The contribution of this study is that it offers SMEs consistent guidelines on how best to conduct relationship management with their customers by using a systemic methodology that can be adapted to the requirements of more effective interaction between a company and its customers. It also provides coherence to the purpose of meeting customers’ needs. This is an action strategy that focuses especially on the use of tools, such as SERVQUAL, Kano and SWOT analysis, and thereby increases the competitive profile of organizations in this sector.

Originality/value

This study is a new approach to customer loyalty for SMEs in the service sector, which integrates elements of CRM strategy and implementation.

Details

Journal of Business & Industrial Marketing, vol. 33 no. 5
Type: Research Article
ISSN: 0885-8624

Keywords

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Article
Publication date: 18 June 2021

Chiranjit Das

The purpose of this study is to analyze the effect of low carbon product design on firm's competitiveness and economic performance. It also examines the mediating role of…

Abstract

Purpose

The purpose of this study is to analyze the effect of low carbon product design on firm's competitiveness and economic performance. It also examines the mediating role of the proactive environmental strategy and eco-innovation on low carbon product design, competitiveness and economic performance.

Design/methodology/approach

Through a questionnaire-based survey, the data were collected from 69 Indian manufacturing firms and analyzed using a variance-based structural equation modeling (SEM) technique to test the proposed hypotheses.

Findings

The results show that the low carbon product design significantly improves firm's competitiveness and economic performance, and proactive environmental strategy significantly mediates the relationship between low carbon product design and firm's competitiveness.

Practical implications

This study provides a framework for the adoption of low carbon product design. It demonstrates how manufacturing firms can implement environmental friendly product design. It also analyses the contextual factors that ensure a successful low carbon product design.

Originality/value

This article investigates the economic benefit of low carbon product design, thus filling lacuna in existing research.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

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Article
Publication date: 20 August 2018

Sebastião M. Neto, Sérgio Dias, Rokia Missaoui, Luis Zárate and Mark Song

In recent years, the increasing complexity of the hyper-connected world demands new approaches for social network analysis. The main challenges are to find new…

Abstract

Purpose

In recent years, the increasing complexity of the hyper-connected world demands new approaches for social network analysis. The main challenges are to find new computational methods that allow the representation, characterization and analysis of these social networks. Nowadays, formal concept analysis (FCA) is considered an alternative to identifying conceptual structures in a social network. In this FCA-based work, this paper aims to show the potential of building computational models based on implications to represent and analyze two-mode networks.

Design/methodology/approach

This study proposes an approach to find three important substructures in social networks such as conservative access patterns, minimum behavior patterns and canonical access patterns. The present study approach considered as a case study a database containing the access logs of a cable internet service provider.

Findings

The result allows us to uncover access patterns, conservative access patterns and minimum access behavior patterns. Furthermore, through the use of implications sets, the relationships between event-type elements (websites) in two-mode networks are analyzed. This paper discusses, in a generic form, the adopted procedures that can be extended to other social networks.

Originality/value

A new approach is proposed for the identification of conservative behavior in two-mode networks. The proper implications needed to handle minimum behavior pattern in two-mode networks is also proposed to be analyzed. The one-item conclusion implications are easy to understand and can be more relevant to anyone looking for one particular website access pattern. Finally, a method for a canonical behavior representation in two-mode networks using a canonical set of implications (steam base), which present a minimal set of implications without loss of information, is proposed.

Details

International Journal of Web Information Systems, vol. 14 no. 3
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 1 August 2006

Amir M. Sharif and Zahir Irani

Noting the scarcity of complexity techniques applied to modelling social systems, this paper attempts to formulate a conceptual model of decision‐making behaviour within…

Abstract

Purpose

Noting the scarcity of complexity techniques applied to modelling social systems, this paper attempts to formulate a conceptual model of decision‐making behaviour within the information systems evaluation (ISE) task, against the backdrop of complexity theory.

Design/methodology/approach

Complexity theory places an emphasis on addressing how dynamic non‐linear systems can be represented and modelled utilising computational tools and techniques to draw out inherent system dynamics. In doing so, the use of fuzzy cognitive mapping (FCM) and morphological analysis (MA) (hence a fuzzy‐morphological approach), is applied to empirical case study data, to elucidate the inherent behavioural and systems issues involved in ISE decision making within a British manufacturing organisation.

Findings

The paper presents results of applying a combined FCM and MA approach to modelling complexity within management decision making in the ISE task: both in terms of a cognitive map of the key decision criteria; a matrix of constraint criteria; and a synthesised model that provides an indication of the linkages between technology management factors and organisational imperatives and goals. These findings show the usefulness of viewing the topic in complexity science terms (emergent behaviour, non‐linearity and chaotic response).

Research limitations/implications

This research is limited in applying the given technique to a single case study organisation in the UK manufacturing sector, where the sample size is limited. Since this is the first time that such a combined MA‐FCM technique has been used in this field known to the authors, future research needs to validate and explore the implications of this approach in a wider context (multiple organisations and viewpoints).

Practical implications

The paper highlights the need for those involved in analysing managerial decision making to include aspects of complexity theory in their evaluations – namely uncovering inherent inter‐relationships that may exist between stakeholders, processes and systems. In doing so, expanding the manager's understanding of how to achieve congruence between driving forces and factors, which may exhibit non‐linear, chaotic or feedback behaviour.

Originality/value

The given research brings together both artificial intelligence and operational research techniques, applied in the socio‐technical milieu of information systems evaluation, within the context of complexity theory, in order to describe the rich detail within the ISE decision‐making task.

Details

Management Decision, vol. 44 no. 7
Type: Research Article
ISSN: 0025-1747

Keywords

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