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Article
Publication date: 10 May 2022

Gordhan K. Saini, Filip Lievens and Mukta Srivastava

In the past 25 years, employer and internal branding have grown significantly. Prior reviews tended to focus on either one of these domains. This study aims to map the…

339

Abstract

Purpose

In the past 25 years, employer and internal branding have grown significantly. Prior reviews tended to focus on either one of these domains. This study aims to map the intellectual structure of research on both employer branding and internal branding, thereby identifying impactful authors and journals, current and evolving themes and avenues for future research.

Design/methodology/approach

Using VOSviewer and Biblioshiny software packages, a bibliometric analysis of 739 articles was conducted using various methods such as citation analysis, bibliographic coupling, cluster analysis, keyword analysis and three-field plot. The Scopus results were further validated using 297 articles produced by the Web of Science data set. It ensured the robustness of the results and generalizability of the findings across bibliometric data sets.

Findings

The findings first report the impactful articles, authors and institutions of employer and internal branding research, along with popular keywords used in this area. Next, the analysis reveals four major clusters and seven subthemes (i.e. employer brand and job seekers, employer brand and employees, employer brand and international human resource management (HRM), third-party employer branding, internal branding – conceptualization/review, internal branding – antecedents and consequences, internal brand management). Early research focused more on “corporate brandings,” whereas current research deals more with “employer branding: antecedents and consequences,” “employer branding conceptualization/review,” and “internal branding” and its subthemes. The employer and internal branding clusters have evolved largely independent from each other. This study offers future research directions and practical implications per cluster.

Originality/value

To the best of the authors’ knowledge, this study is the first comprehensive bibliometric analysis of both employer and internal branding research.

Details

Journal of Product & Brand Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1061-0421

Keywords

Article
Publication date: 14 April 2022

Reza Kiani Mavi, Neda Kiani Mavi, Doina Olaru, Sharon Biermann and Sae Chi

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies…

Abstract

Purpose

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.

Design/methodology/approach

Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.

Findings

The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.

Research limitations/implications

Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.

Originality/value

This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 15 November 2021

Anna Corinna Cagliano, Giulio Mangano, Carlo Rafele and Sabrina Grimaldi

The objective of this paper is to propose an approach to comparatively analyze the performance of drugs and consumable products warehouses belonging to different…

Abstract

Purpose

The objective of this paper is to propose an approach to comparatively analyze the performance of drugs and consumable products warehouses belonging to different healthcare institutions.

Design/methodology/approach

A Cluster Analysis is completed in order to classify warehouses and identify common patterns based on similar organizational characteristics. The variables taken into account are associated with inventory levels, the number of SKUs, and incoming and outgoing flows.

Findings

The outcomes of the empirical analysis are confirmed by additional indicators reflecting the demand level and the associated logistics flows faced by the warehouses at issue. Also, the warehouses belonging to the same cluster show similar behaviors for all the indicators considered, meaning that the performed Cluster Analysis can be considered as coherent.

Research limitations/implications

The study proposes an approach aimed at grouping healthcare warehouses based on relevant logistics aspects. Thus, it can foster the application of statistical analysis in the healthcare Supply Chain Management. The present work is associated with only one regional healthcare system.

Practical implications

The approach might support healthcare agencies in comparing the performance of their warehouses more accurately. Consequently, it could facilitate comprehensive investigations of the managerial similarities and differences that could be a first step toward warehouse aggregation in homogeneous logistics units.

Originality/value

This analysis puts forward an approach based on a consolidated statistical tool, to assess the logistics performances in a set of warehouses and, in turn to deepen the related understanding as well as the factors determining them.

Details

The International Journal of Logistics Management, vol. 33 no. 1
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 13 October 2021

Brady Lund and Jinxuan Ma

This literature review explores the definitions and characteristics of cluster analysis, a machine-learning technique that is frequently implemented to identify groupings…

Abstract

Purpose

This literature review explores the definitions and characteristics of cluster analysis, a machine-learning technique that is frequently implemented to identify groupings in big datasets and its applicability to library and information science (LIS) research. This overview is intended for researchers who are interested in expanding their data analysis repertory to include cluster analysis, rather than for existing experts in this area.

Design/methodology/approach

A review of LIS articles included in the Library and Information Source (EBSCO) database that employ cluster analysis is performed. An overview of cluster analysis in general (how it works from a statistical standpoint, and how it can be performed by researchers), the most popular cluster analysis techniques and the uses of cluster analysis in LIS is presented.

Findings

The number of LIS studies that employ a cluster analytic approach has grown from about 5 per year in the early 2000s to an average of 35 studies per year in the mid- and late-2010s. The journal Scientometrics has the most articles published within LIS that use cluster analysis (102 studies). Scientometrics is the most common subject area to employ a cluster analytic approach (152 studies). The findings of this review indicate that cluster analysis could make LIS research more accessible by providing an innovative and insightful process of knowledge discovery.

Originality/value

This review is the first to present cluster analysis as an accessible data analysis approach, specifically from an LIS perspective.

Details

Performance Measurement and Metrics, vol. 22 no. 3
Type: Research Article
ISSN: 1467-8047

Keywords

Article
Publication date: 24 February 2021

Syed Asif Raza and Srikrishna Madhumohan Govindaluri

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends…

Abstract

Purpose

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics.

Design/methodology/approach

More than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included.

Findings

The findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC.

Practical implications

This research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies.

Originality/value

The paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.

Details

Benchmarking: An International Journal, vol. 28 no. 9
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 7 June 2021

Syed Asif Raza

The findings of this paper throw light on the focal research areas within RFID in the supply chain, which serves as an effective guideline for future research in this…

Abstract

Purpose

The findings of this paper throw light on the focal research areas within RFID in the supply chain, which serves as an effective guideline for future research in this area. This research, therefore, contributes to filling the gap by carrying out an SLR of contemporary research studies in the area of RFID applications in supply chains. To date, SLR augmented with BA has not been used to study the developments in RFID applications in supply chains.

Design/methodology/approach

We analyze 556 articles from years 2001 to date using Systematic Literature Review (SLR). Contemporary bibliometric analysis (BA) tools are utilized. First, an exploratory analysis is carried, out revealing influential authors, sources, regions, among other key aspects. Second, a co-citation work analysis is utilized to understand the conceptual structure of the literature, followed by a dynamic co-citation network to reveal the evolution of the field. This is followed by a multivariate analysis is performed on top-100 cited papers, and k-means clustering is carried out to find optimal groups and identify research themes. The influential themes are then pointed out using factor analysis.

Findings

An exploratory analysis is carried out using BA tools to provide insights into factors such as influential authors, production countries, top-cited papers and frequent keywords. Visualization of bibliographical data using co-citation network analysis and keyword co-occurrence analysis assisted in understanding the groups (communities) of research themes. We employed k-means clustering and factor analysis methods to further develop these insights. A historiographical direct citation analysis also unveils potential research directions. We observe that RFID applications in the supply chain are likely to benefit from the Internet of Things and blockchain Technology along with the other machine learning and visualization approaches.

Originality/value

Although several researchers have researched RFID literature in relation to supply chains, these reviews are often conducted in the traditional manner where the author(s) select paper based on their area of expertise, interest and experience. Limitation of such reviews includes authors’ selection bias of studies to be included and limited or no use of advanced BA tools for analysis. This study fills this research gap by conducting an SLR of RFID in supply chains to identify important research trends in this field through the use of advanced BA tools.

Details

Journal of Enterprise Information Management, vol. 35 no. 2
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 16 March 2015

Stefan Klotz and Andreas Lindermeir

This paper aims to improve decision making in credit portfolio management through analytical data-mining methods, which should be used as data availability and data…

1360

Abstract

Purpose

This paper aims to improve decision making in credit portfolio management through analytical data-mining methods, which should be used as data availability and data quality of credit portfolios increase due to (semi-)automated credit decisions, improved data warehouses and heightened information needs of portfolio management.

Design/methodology/approach

To contribute to this fact, this paper elaborates credit portfolio analysis based on cluster analysis. This statistical method, so far mainly used in other disciplines, is able to determine “hidden” patterns within a data set by examining data similarities.

Findings

Based on several real-world credit portfolio data sets provided by a financial institution, the authors find that cluster analysis is a suitable method to determine numerous multivariate contract specifications implying high or, respectively, low profit potential.

Research limitations/implications

Nevertheless, cluster analysis is a statistical method with multiple possible settings that have to be adjusted manually. Thus, various different results are possible, and as cluster analysis is an application of unsupervised learning, a validation of the results is hardly possible.

Practical implications

By applying this approach in credit portfolio management, companies are able to utilize the information gained when making future credit portfolio decisions and, consequently, increase their profit.

Originality/value

The paper at hand provides a unique structured approach on how to perform a multivariate cluster analysis of a credit portfolio by considering risk and return simultaneously. In this context, this procedure serves as a guidance on how to conduct a cluster analysis of a credit portfolio including advices for the settings of the analysis.

Details

The Journal of Risk Finance, vol. 16 no. 2
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 12 April 2013

Rekha Mittal

The purpose of this paper is to explore and map the intellectual structure of biofuel research.

547

Abstract

Purpose

The purpose of this paper is to explore and map the intellectual structure of biofuel research.

Design/methodology/approach

The study attempts to present the structure of biofuel research through document co‐citation patterns of core references. Document co‐citation analysis was performed using the Web of Science of the Thomson‐ISI database. A sample of 26 cited references was identified and the co‐citation frequencies were analyzed and represented them systematically within groups of similar researched topics.

Findings

The study shows the co‐citation analysis method suitable for depicting structure of biofuel research in document clusters by performing multivariate analysis: cluster analysis, factor analysis, multidimensional scaling and network analysis.

Research limitations/implications

The study is limited to research articles and co‐citation data for the first author only. For the co‐citation analysis, the cited references rather than the cited authors were used as the units for analysis.

Practical implications

Co‐citational analysis using multivariate tools provides a useful technique to explore and document the development of the field supplementing the insights normally available from the routine co‐citational analysis.

Originality/value

Specialties in biofuel research are identified and this may provide a valuable building block for future research.

Article
Publication date: 2 April 2015

Jennifer L. Duncan, Bharath M. Josiam, Young Hoon Kim and Alexandria C. Kalldin

Focussing on behaviors and attitudes of casual dining patrons, the purpose of this paper is to use a factor-cluster approach to segment patrons into market groups and…

1196

Abstract

Purpose

Focussing on behaviors and attitudes of casual dining patrons, the purpose of this paper is to use a factor-cluster approach to segment patrons into market groups and attempts to determine if differences exist in motivational factors among segments.

Design/methodology/approach

Factor-cluster analysis is an alternative segmentation method to more traditionally used methods based on consumer demographics. Push and pull motivators were analyzed through factor analysis to determine important groupings. Then, to identify homogenous subgroups, k-means cluster analysis was conducted to segment 559 survey respondents based on factor importance.

Findings

Three diverse groups were identified: Fraternizing Kitchen Fearfuls, Functional Feasters, and Foodie Fanatics. The various push and pull factors appeared to affect segments differently, with each cluster ascribing various importance levels to each of the factors used in the clustering approach.

Research limitations/implications

Limitations include the use of a convenience sample and on-campus sampling. Future research should use random sampling methods and obtain surveys from sites not associated with a college campus.

Practical implications

Though not often used in hospitality research, factor-cluster analysis can be useful to segment diners based on behavioral intentions and attributes, allowing marketers to more accurately target these diverse consumer segments. Marketing implications for casual dining restaurants are suggested.

Originality/value

Using the involvement construct with push/pull motivators, this study groups respondents though factor-cluster analysis. Though used in tourism studies, factor-cluster analysis has yet to be studied in the context of casual dining restaurant patrons.

Details

British Food Journal, vol. 117 no. 4
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 6 July 2012

Sascha Kraus, Matthias Filser, Fabian Eggers, Gerald E. Hills and Claes M. Hultman

Entrepreneurial marketing (EM) is at the brink of becoming an established discipline. To advance the field further and to better guide research efforts in different sub…

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Abstract

Purpose

Entrepreneurial marketing (EM) is at the brink of becoming an established discipline. To advance the field further and to better guide research efforts in different sub categories, the purpose of this paper is to examine the field's intellectual structure with the help of citation and co‐citation analysis.

Design/methodology/approach

This paper is based on a two‐stage research design. First a citation analysis is carried out through which thematic clusters are identified. In a second step a co‐citation analysis is conducted to determine the intellectual structure of EM research.

Findings

This study exposes the most influential authors and publications and emphasizes conjunctions among scholars and their findings. Results show three streams that are the foundation of EM research: theoretical foundations of management, entrepreneurship, and marketing; the research interface of marketing and entrepreneurship; SME and new venture marketing.

Research limitations/implications

The results of a bibliometric analysis are limited by the publications that have been selected as a starting point. However, through the selection criteria chosen to identify the database for analysis, the authors are confident that the results illustrate the intellectual structure of EM research in its entirety. The authors recommend that future research should be conducted in one of the three sub‐fields identified in this study.

Practical implications

By laying out different research streams within EM it is hoped that future research will be guided in different directions. “Fine‐tuning” of research efforts will benefit small, new, and entrepreneurial firms.

Originality/value

The analyses conducted in this paper draw a picture of the field that is based on a quantitative approach and therefore sets itself apart from other literature reviews that have a qualitative core.

Details

Journal of Research in Marketing and Entrepreneurship, vol. 14 no. 1
Type: Research Article
ISSN: 1471-5201

Keywords

1 – 10 of over 45000