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Record W3090933020 · doi:10.20491/isarder.2020.1009

Niş Pazarlama Yaklaşımının Bibliyometrik Analiz İle İncelenmesi (The Review of Niche Marketing Approach With Bibliometric Analysis)

2020· article· tr· W3090933020 on OpenAlexaboutno aff
Resul Öztürk

Bibliographic record

VenueJournal of Business Research - Turk · 2020
Typearticle
Languagetr
FieldSocial Sciences
TopicHalal products and consumer behavior
Canadian institutionsnot available
Fundersnot available
KeywordsNicheBusinessBusiness administrationChemistry

Abstract

fetched live from OpenAlex

Amaç – Bu çalışmanın amacı, pazarlama literatüründe yer alan niş pazarlama yazınındaki ana
\ntemaları belirleyip pazarlama alanında niş pazarlama kavramına yönelik gelecek araştırmalara
\nkavramsal bir çerçeve hazırlamaktır.
\nYöntem – Nicel araştırma yönteminin kullanıldığı bu çalışmada araştırmanın amacı doğrultusunda
\nVOSviewer 1.6.15 yazılım programı aracılığıyla bibliyometrik analiz yöntemi kullanılmıştır. Web of
\nScience Core Collection veri tabanında yer alan tüm çalışmalar (makale, bildiri, kitap incelemesi vs.)
\nBoolean taraması temel alınarak “niche marketing” şeklinde konu başlığı olarak taranmıştır. 1983-
\n2020 yılları arasındaki 32 çalışma ortak atıf, yazar ve varlık ile bibliyografik eşleme analizleri
\nbibliyometrik analiz yöntemi ile incelenmiştir.
\nBulgular – Araştırma sonuçları niş pazarlama ile ilgili olarak 2017 yılından itibaren yapılan
\nçalışmalarda artış yaşandığını, çalışmaların yaygın olarak ABD’de yapıldığını, Anzuka, Cuthbert ve
\nHsu gibi yazarların literatüre en çok katkı yapan yazarlar arasında yer aldığını, Brown (1995), Drea
\nve Hanna (2000), Hollingsworth (2001), Eaton (2006), Malin (2010) ve Anzaku ve Salau’nun (2017)
\nçalışmalarının en çok atıf alan çalışmalar olduğunu, Kanada, Yeni Zelanda, Çin ve Türkiye gibi
\nülkelerde en fazla atıf yapıldığını, tarım, giyim, tekstil, bilgi teknolojileri gibi kavramların bir arada
\nkullanıldığını göstermiştir.
\nTartışma – Niş pazarlama, son yıllarda teorik çalışmalarda artış yaşandığı bir çalışma alanı olsa da
\nbu alanda sınırlı sayıda çalışmanın olduğu düşünüldüğünde gerek pazarlama uygulayıcıları
\ngerekse akademisyenler açısından araştırılması ve incelenmesi gereken, işletmelere farklı sektörler
\nve pazar bölümlerinde rekabet avantajı sağlayabilecek bir konu olarak karşımıza çıkmaktadır. 
\n
\nPurpose – The aim of this study is to determine the main themes in the niche marketing literature in
\nthe marketing literature and to prepare a conceptual framework for future research in the field of
\nmarketing in the field of niche marketing.
\nDesign/methodology/approach – In this study, in which quantitative research method was used,
\nfor the purpose of the research, the bibliometric analysis method was used through the VOSviewer
\n1.6.15 software program. All the studies (articles, papers, book reviews, etc.) in the Web of Science
\nCore Collection database have been scanned as “niche marketing” based on Boolean scanning.
\nBetween 1983 and 2020, 32 studies were analyzed by bibliometric analysis method with co-citation,
\nco-authorship and co-occurence, and bibliographic coupling analysis.
\nFindings – The results of the research show that there has been an increase in studies on niche
\nmarketing since 2017; studies are widely done in the USA; the authors like Anzuka, Cuthbert and
\nHsu are among the most contributing authors to the literature; Brown (1995), Drea and Hanna (2000),
\nHollingsworth (2001), Eaton (2006), Malin (2010) and Anzaku and Salau (2017) are the most cited
\nstudies; most reference was made in countries such as Canada, New Zealand, China and Turkey; it
\nshowed that concepts such as agriculture, clothing, textile, information technologies are used
\ntogether.
\nDiscussion – Although niche marketing is a field of study in which there has been an increase in
\ntheoretical studies in recent years, considering the limited number of studies in this field, it emerges
\nas a subject that needs to be researched and examined in terms of both marketing practitioners and
\nacademics, which can provide businesses with competitive advantage in different sectors and
\nmarket segments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0710.693
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.157
GPT teacher head0.397
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

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