Example of International Journal of Information and Decision Sciences format
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Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format
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Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format Example of International Journal of Information and Decision Sciences format
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This content is only for preview purposes. The original open access content can be found here.
open access Open Access

International Journal of Information and Decision Sciences — Template for authors

Categories Rank Trend in last 3 yrs
Management of Technology and Innovation #188 of 248 down down by 41 ranks
Information Systems and Management #98 of 125 down down by 28 ranks
Strategy and Management #358 of 440 down down by 65 ranks
Computer Science Applications #582 of 693 down down by 107 ranks
journal-quality-icon Journal quality:
Low
calendar-icon Last 4 years overview: 71 Published Papers | 58 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 27/06/2020
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FAQ

Related Journals

open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 5.0
SJR: 0.788
SNIP: 1.115
open access Open Access

Wiley

Quality:  
High
CiteRatio: 4.2
SJR: 1.238
SNIP: 1.377
open access Open Access

Inderscience Publishers

Quality:  
Medium
CiteRatio: 1.6
SJR: 0.264
SNIP: 0.486

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.8

27% from 2019

CiteRatio for International Journal of Information and Decision Sciences from 2016 - 2020
Year Value
2020 0.8
2019 1.1
2018 1.0
2017 0.7
2016 0.9
graph view Graph view
table view Table view

0.223

12% from 2019

SJR for International Journal of Information and Decision Sciences from 2016 - 2020
Year Value
2020 0.223
2019 0.252
2018 0.369
2017 0.233
2016 0.215
graph view Graph view
table view Table view

0.287

49% from 2019

SNIP for International Journal of Information and Decision Sciences from 2016 - 2020
Year Value
2020 0.287
2019 0.566
2018 0.673
2017 0.58
2016 0.385
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has decreased by 27% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 12% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 49% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
International Journal of Information and Decision Sciences

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Inderscience Publishers

International Journal of Information and Decision Sciences

Approved by publishing and review experts on SciSpace, this template is built as per for International Journal of Information and Decision Sciences formatting guidelines as mentioned in Inderscience Publishers author instructions. The current version was created on 27 Jun 2020 and has been used by 361 authors to write and format their manuscripts to this journal.

i
Last updated on
27 Jun 2020
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ISSN
1756-7017
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
plainnat
i
Citation Type
Author Year
(Blonder et al., 1982)
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Bibliography Example
Beenakker, C. W. J. (2006). ‘Specular Andreev Reflection in Graphene’. Phys. Rev. Lett., Vol 97, No 6, pp. 067007.

Top papers written in this journal

Journal Article DOI: 10.1504/IJIDS.2018.090667
Data normalisation techniques in decision making: case study with TOPSIS method
Nazanin Vafaei1, Rita A. Ribeiro1, Luis M. Camarinha-Matos1

Abstract:

Data normalisation is essential for decision-making methods because data has to be numerical and comparable to be aggregated into a single score per alternative. In multi-criteria decision-making (MCDM), normalisation must convert criteria values into a common scale, thus, enabling rating and ranking of alternatives. Therefor... Data normalisation is essential for decision-making methods because data has to be numerical and comparable to be aggregated into a single score per alternative. In multi-criteria decision-making (MCDM), normalisation must convert criteria values into a common scale, thus, enabling rating and ranking of alternatives. Therefore, it is a challenge to select a suitable normalisation technique to represent an appropriate mapping from source data to a common scale. There are some attempts in the literature to address the subject of normalisation, but it is still an open question which technique is more appropriate for any MCDM method. Our research contribution is an assessment approach for evaluating normalisation techniques. Here, we focus on six well-known normalisation techniques and on TOPSIS method. The proposed assessment process provides a more robust evaluation and selection of the best normalisation technique for usage in TOPSIS. read more read less

Topics:

TOPSIS (65%)65% related to the paper, Multiple-criteria decision analysis (50%)50% related to the paper
View PDF
78 Citations
Journal Article DOI: 10.1504/IJIDS.2019.101994
Impact of social media on consumer behaviour

Abstract:

The goal of this paper is to research empirically the role of social media in consumers' decision-making process for complex purchases - those characterised by significant brand differences, high c... The goal of this paper is to research empirically the role of social media in consumers' decision-making process for complex purchases - those characterised by significant brand differences, high c... read more read less

Topics:

Consumer behaviour (63%)63% related to the paper, Social media (54%)54% related to the paper
52 Citations
Journal Article DOI: 10.1504/IJIDS.2020.10029122
Decision tree classifier: a detailed survey
Priyanka1, Dharmender Kumar1

Abstract:

Decision tree classifier (DTC) is one of the well-known methods for data classification. The most significant feature of DTC is its ability to change the complicated decision making problems into simple processes, thus finding a solution which is understandable and easier to interpret. This paper provides a brief review on va... Decision tree classifier (DTC) is one of the well-known methods for data classification. The most significant feature of DTC is its ability to change the complicated decision making problems into simple processes, thus finding a solution which is understandable and easier to interpret. This paper provides a brief review on various algorithms developed in literature for constructing and representing decision trees, splitting criteria for selecting best attribute and pruning methods. The readers will be able to understand why decision trees are more popular among all other methods of classification, what are their uses, limitations and applications in different diverse areas. They will also come to know about a decision tree induction algorithms, splitting criteria, pruning methods, concepts of ensemble methods, fuzzy decision trees, hybridisation of DTCs, etc. These enhancements are found very helpful in solving complex datasets with less computation in very short time period while achieving high accuracy. read more read less

Topics:

Decision tree learning (65%)65% related to the paper, Pruning (decision trees) (65%)65% related to the paper, Decision tree (65%)65% related to the paper, Ensemble learning (53%)53% related to the paper, Data classification (51%)51% related to the paper
45 Citations
Journal Article DOI: 10.1504/IJIDS.2011.041586
A fully fuzzified data envelopment analysis model
Adel Hatami-Marbini1, Madjid Tavana2, Alireza Ebrahimi3

Abstract:

In the conventional data envelopment analysis (DEA), all the data assumes the form of crisp numerical values. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Some researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data... In the conventional data envelopment analysis (DEA), all the data assumes the form of crisp numerical values. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Some researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA by constructing linear programming (LP) models with 'partial' fuzzy parameters. The main purpose of this study is to evaluate the performance of a set of decision making units (DMUs) in a fully fuzzified environment. We propose a novel fully fuzzified DEA (FFDEA) model by utilising a fully fuzzified LP (FFLP) model, where all decision parameters and variables are fuzzy numbers. The contribution of this paper is threefold: first, we consider ambiguous, uncertain and imprecise input and output data in DEA; second, we address the gap in the fuzzy DEA literature for solutions to fully fuzzified problems; and third, we present a numerical example to demonstrate the applicability and efficacy of the proposed model. read more read less

Topics:

Fuzzy number (63%)63% related to the paper, Fuzzy logic (59%)59% related to the paper, Data envelopment analysis (58%)58% related to the paper, Linear programming (51%)51% related to the paper
35 Citations
Journal Article DOI: 10.1504/IJIDS.2008.020050
Supply Chain Risk Management
Thomas Yew Sing Lee1

Abstract:

The existing models utilise a mean value approach with deterministic failure cost to determine the optimal number of suppliers in the presence of supplier failure risks. The mean value approach assumes, the firm has a linear utility function with respect to the supply disruptions. For major disruptions that could threaten the... The existing models utilise a mean value approach with deterministic failure cost to determine the optimal number of suppliers in the presence of supplier failure risks. The mean value approach assumes, the firm has a linear utility function with respect to the supply disruptions. For major disruptions that could threaten the survival of the firm, the linearity assumption is questionable. Furthermore, the operating cost of working with the suppliers and the financial loss cause by failure of suppliers are subject to uncertainty. This article utilises the mean-variance approach to determine the optimal set of suppliers in the presence of supplier failure risks. The importance of cash-flow variability in the supplier selection/planning process is considered explicitly. Our methodology allows us to balance the two desirable, but conflicting objectives of cost minimisation and service levels achieved. Furthermore, traditional risk management tools like insurance are incorporate into the optimal suppliers' selection process. read more read less

Topics:

Supplier relationship management (65%)65% related to the paper, Supply chain (58%)58% related to the paper, Supply chain risk management (57%)57% related to the paper, Risk management (54%)54% related to the paper, Supply chain management (54%)54% related to the paper
35 Citations
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International Journal of Information and Decision Sciences format uses plainnat citation style.

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Frequently asked questions

1. Can I write International Journal of Information and Decision Sciences in LaTeX?

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2. Do you follow the International Journal of Information and Decision Sciences guidelines?

Yes, the template is compliant with the International Journal of Information and Decision Sciences guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in International Journal of Information and Decision Sciences?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the International Journal of Information and Decision Sciences citation style.

4. Can I use the International Journal of Information and Decision Sciences templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for International Journal of Information and Decision Sciences.

5. Can I use a manuscript in International Journal of Information and Decision Sciences that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper International Journal of Information and Decision Sciences that you can download at the end.

6. How long does it usually take you to format my papers in International Journal of Information and Decision Sciences?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in International Journal of Information and Decision Sciences.

7. Where can I find the template for the International Journal of Information and Decision Sciences?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per International Journal of Information and Decision Sciences's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the International Journal of Information and Decision Sciences's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. International Journal of Information and Decision Sciences an online tool or is there a desktop version?

SciSpace's International Journal of Information and Decision Sciences is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

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After writing your paper autoformatting in International Journal of Information and Decision Sciences, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is International Journal of Information and Decision Sciences's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for International Journal of Information and Decision Sciences?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for International Journal of Information and Decision Sciences. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In International Journal of Information and Decision Sciences?

The 5 most common citation types in order of usage for International Journal of Information and Decision Sciences are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the International Journal of Information and Decision Sciences?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per International Journal of Information and Decision Sciences's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download International Journal of Information and Decision Sciences in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in International Journal of Information and Decision Sciences Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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