Antecedents of mobile advertising value: a precedence analysis using the hybrid RIDIT-GRA approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anshuman Sharma ◽  
Vivek Kumar Pathak ◽  
Mohammad Qutubuddin Siddiqui
Keyword(s):  
Communication Technologies ◽  
Shopping Mall ◽  
Mobile Advertising ◽  
Mobile Platforms ◽  
Content Type ◽  
Relational Analysis ◽  
Priority Ranking ◽  
Intercept Survey ◽  
Grey Relational ◽  
Practical Implications

Purpose Massive transformations in mobile communication technologies have forced marketers to recognize and emphasize the factors that influence consumers’ perception of advertising value. This paper aims to explore and rank the various antecedents of advertising value as perceived by consumers to offer meaningful conclusions to marketers on mobile platforms. Design/methodology/approach Responses were collected from 483 consumers using a shopping mall intercept survey and analyzed using SPSS to confirm reliability, validity and data reduction. The Relative to an Identified Distribution (RIDIT) analysis and Grey Relational Analysis (GRA) methods were then applied to prioritize the scale items of the antecedents of mobile advertising value. Findings Five antecedents of advertising value were found: credibility, entertainment, informativeness, irritation and message relevance. A priority ranking was allotted to the antecedents’ scale items using the RIDIT analysis and was verified via GRA results with a correlation of 98% between the rankings of the two independent methodologies. Practical implications The findings provide a roadmap to determine which antecedents of mobile advertising value have a higher or lower impact on consumers’ overall perceptions of the advertisements they are exposed to on mobile platforms. Originality/value This study aims to use first-hand data to prioritize the underlying antecedents of mobile advertising value, which has rarely been done to the best of the authors’ knowledge. It also used two different approaches in a single study to rank the dimensions, thus producing more valid results.

Performance of TV programs: a robust MCDM approach

2020 ◽  
Vol 27 (3) ◽  
pp. 1188-1209 ◽  
Author(s):  
Liz Hassad de Andrade ◽  
Jorge Junio Moreira Antunes ◽  
Peter Wanke
Keyword(s):  
Principal Component ◽  
Performance Criteria ◽  
Data Set ◽  
Long Tail ◽  
Content Type ◽  
Relational Analysis ◽  
Complex Decision ◽  
Grey Relational ◽  
First Time ◽  
Practical Implications

PurposeThe aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.Design/methodology/approachThe Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Ng-model, Grey relational analysis (GRA), and principal component analysis (PCA) were applied to evaluate the programs, using audience, share, and duration as the performance criteria.FindingsBy comparing TOPSIS to the Ng-model, PCA, and GRA, we verified that SVD and bootstrap SVD TOPSIS provide a good balance between equal-weights TOPSIS and the other models. This is because SVD and bootstrap SVD TOPSIS break down the data to a higher degree, but are less impacted by outliers compared to the long tail models.Practical implicationsTo determine which TV programs should be replaced or modified is a complex decision that has not been addressed in the literature. The advantage of using a multi-criteria decision-making (MCDM) approach is that analysts can choose as many criteria as they want to rank TV programs, rather than relying on a single criterion (e.g., audience, share, target rating point).Originality/valueThis work represents the first time that robust MCDM methodology is applied to an audience data set to analyze the performance of TV programs and to identify what can be done to improve them. This study shows the application of a detailed methodology that is useful for the improvement of TV programs and other entertainment industry content.

Financial performance assessment using Grey relational analysis (GRA)

2019 ◽  
Vol 9 (4) ◽  
pp. 502-516 ◽  
Author(s):  
Anandarao Suvvari ◽  
Raja Sethu Durai S. ◽  
Phanindra Goyari
Keyword(s):  
Performance Analysis ◽  
Financial Performance ◽  
Life Insurance ◽  
Grey Relational Analysis ◽  
Statistical Distribution ◽  
Insurance Companies ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Practical Implications

Purpose Traditional statistical methods to study the financial performance of any industry have many barriers and limitations in terms of the statistical distribution of the financial ratios, and, in particular, it considers only its positive values of it. The purpose of this paper is to estimate the financial performance of 24 Indian life insurance companies for the period from 2013 to 2016 using Grey relational analysis (GRA) proposed by Deng (1982) that accommodates the negative values in the analysis. Design/methodology/approach Financial performance of 24 Indian life insurance companies for the years from 2013–2014 to 2015–2016 is examined using a total of 14 indicators from capital adequacy ratios, liquidity ratios, operating ratios and profitability ratios (PR). The methodology used is GRA to obtain the Grey grades to rank the performance indicators, where higher relational grade shows better financial performance, and a lower score depicts the scope for improving the performance. Findings The results rank the insurance companies according to their financial performance in which Shriram insurance stands first with higher relational grade score, followed by the companies like IDBI Insurance, Sahara Insurance and Life Insurance Corporation of India. The main finding is that PR which have negative values are playing a crucial role in determining the financial performance of Indian life insurance companies. Practical implications This study has far-reaching practical implications in twofold: first, for the Indian life insurance industry, they have to concentrate more on PR for better financial health and, second, for any financial performance analysis, ignoring negative value ratios produce biased inference and GRA can be used for better inference. Originality/value This study is the first attempt to evaluate the financial performance of Indian life insurance using the GRA methodology. The advantage of GRA is that there is no restrictions on the statistical distribution of the data and it also accommodates the negative values, whereas all the other traditional methods insist on the statistical distribution of data, and, more importantly, they cannot handle negative values in the performance analysis.

Modeling of the machining parameters in turning of Al-5052/TiC/SiC composites: a statistical modeling approach using grey relational analysis (GRA) and response surface methodology (RSM)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Venkateshwar Reddy Pathapalli ◽  
Meenakshi Reddy Reddigari ◽  
Eswara Kumar Anna ◽  
P. Srinivasa Rao ◽  
D V. Ramana Reddy
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Content Type ◽  
Relational Analysis ◽  
Desirability Approach ◽  
Grey Relational ◽  
Grey Taguchi

PurposeMetal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.Design/methodology/approachThe combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.FindingsThe contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.Practical implicationsThe results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.Originality/valueThe originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.

Optimization of process parameters of powder mixed EDM for high carbon high chromium alloy steel (D2 steel) through GRA approach

2018 ◽  
Vol 8 (4) ◽  
pp. 388-398 ◽  
Author(s):  
Kanwal Jit Singh
Keyword(s):  
Material Removal ◽  
Removal Rate ◽  
Chromium Alloy ◽  
High Carbon ◽  
Content Type ◽  
Practical Applications ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational ◽  
D2 Steel

Purpose The purpose of this paper is to investigate the process parameters and optimise the machining input parameter of powder mixed electric discharge machining for high carbon high chromium alloy steel (D2 steel) for the industrial application. Grey relational analysis approach has been used to obtain the multiple performance output response. Design/methodology/approach In this experimental work, input parameters, namely, pulse on-time, discharge current, tool material and grit size, are selected. The design of the experiment has been constructed with the help of MINITAB 7 Software, in which L16 orthogonal array has been preferred for the experimentation. The effect of input parameters, namely, material removal rate, tool wear rate and surface roughness, is investigated. Grey relational analysis and analysis of variance are performed to optimise the input parameters and better output results. Findings In this experimentation, there is an increment of tool wear rate by 64.49 per cent, material removal rate by 47.14 per cent and surface roughness by 35.82 per cent. Practical implications A lot of practical applications have been found in many different material processing industries like metallurgy, machinery, electronics, transportation, military science, agricultural machinery, etc. These practical applications have brought forward definite and noticeable economic benefits. Originality/value The reader is given a general overview on the machining investigation and optimisation of processes parameters through the grey theory approach. It gives a new framework to investigate the problems where multiple input machining variable and various output responses are obtained in single optimised parameters.

Quality improvement of smart senior care service platform in China based on grey relational analysis and Fuzzy-QFD

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lan Xu ◽  
Yu Zhang
Keyword(s):  
Quality Improvement ◽  
Grey Relational Analysis ◽  
Care Service ◽  
The Elderly ◽  
Service Platform ◽  
Content Type ◽  
Relational Analysis ◽  
Improvement Method ◽  
Grey Relational ◽  
Quality Improvement Method

PurposeSmart senior care industry in China currently faces a series of practical difficulties such as an imbalance in the demand and supply structure, service products unable to cater to the actual needs of the elderly and a low degree of marketization. This study therefore proposes using grey relational analysis and the Fuzzy-quality function development (QFD) quality improvement method to help solve these problems.Design/methodology/approachThe proposed method converts the fuzzy requirements of the elderly into the technical characteristics of technologically augmented senior care service products. It then, uses the QFD relationship matrix, combined with grey relational analysis, to analyze the relationship between the needs of elderly and the converted technical characteristics, and subsequently identifies key technical characteristics.FindingsResults show that an improvement in the smart senior care service platform according to the differences of the elderly's preferences can significantly improve users' satisfaction with the service in addition to enhancing market competitiveness of the technologically assisted senior care service products.Originality/valueA novel method to improve the need of smart senior care is proposed by considering age difference. The proposed grey relational analysis and Fuzzy-QFD quality improvement method can help improve the service quality of the smart senior care service platform.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

Increasing brand recall for naming rights sponsorships

2016 ◽  
Vol 6 (4) ◽  
pp. 377-389 ◽  
Author(s):  
Robert J. Donovan ◽  
Julia Anwar-McHenry ◽  
Yolexis Hernandez Aguilera ◽  
Amberlee Nicholas ◽  
Simone Kerrigan
Keyword(s):  
Social Marketing ◽  
Design Methodology ◽  
Brand Name ◽  
Content Type ◽  
Brand Recall ◽  
Intercept Survey ◽  
Promotional Materials ◽  
Naming Rights ◽  
Social Marketing Campaigns ◽  
Practical Implications

Purpose Maximising return on naming rights sponsorships is important for social marketing campaigns with limited funds. Naming rights allow the sponsor’s brand to be aligned with the event name in text and visual promotional materials. For visual displays, either the brand logo or the brand name in words can be aligned with the event name. As the Act–Belong–Commit mental health promotion campaign’s logo encapsulates the brand name, a study was conducted to assess the relative impact on recall of “Act–Belong–Commit” as part of a sponsored event name, when the logo was aligned with the event name versus when the brand name in only words was aligned with the event name. Design/methodology/approach An intercept survey was conducted with n = 112 adult university students. Participants were presented with one of the above two branding alignments for the sponsored event. The image was removed from view, a distracter question asked and participants were asked to recall the name of the event. Findings Recall of the Act–Belong–Commit brand in full as part of the name of the event was significantly and substantially greater for participants exposed to the words only alignment versus the logo alignment: 52 vs 7 per cent (p < 0.000). Practical implications Given these findings, the campaign has adopted the policy of using the words Act–Belong–Commit alongside the event name rather than the logo in future naming rights sponsorships. Originality/value It is recommended that other social marketing brands with similar brand/logo designs undertake research to ensure optimal return on naming rights sponsorships.

Application of grey relational analysis to expose individual student's cognitive difficulties in English public speaking

2014 ◽  
Vol 4 (2) ◽  
pp. 232-249
Author(s):  
Yow-jyy Joyce Lee ◽  
Lawrence W. Lan
Keyword(s):  
Grey Relational Analysis ◽  
Teaching And Learning ◽  
Public Speaking ◽  
Learning Difficulties ◽  
Cognitive Learning ◽  
Content Type ◽  
Cognitive Difficulties ◽  
Relational Analysis ◽  
Grey Relational ◽  
Grey Relation

Purpose – The purpose of this paper is to propose a formative assessment framework to expose individual student's cognitive learning difficulties in English public speaking. The paper aims to provide student feedback and information during the teaching and learning process. A grey student-construct (S-C) chart is developed to represent the students’ cognitive mapping of the speech difficulties in relation to their overall speech conceptualization. This grey S-C chart can facilitate the instructors to ameliorate the classroom teaching and learning performance in English public speaking. Design/methodology/approach – In total, 26 students in a class of English Speech and Rhetoric participate in the experiment – each student views the online video segments of a great speaker's speech, and then decides what segments would best support the speaking skill constructs and also reflects on his/her own difficulties in the same constructs. The grey relational analysis (GRA) method is used to analyze the empirical data. The individual student's construct localization grey relation grade values are calculated to rank the grey relation for both students and constructs. Accordingly, a grey S-C matrix is constructed and a grey S-C chart can thus be developed. Findings – The grey S-C chart manifestly displays the cognitive difficulties in sequences of both students and constructs. Practical implications – According to the grey S-C chart, the instructors may modify teaching strategies to enhance the overall classroom performance. The students may adjust learning strategies to eliminate their specific difficulties. Offering individualized advanced and remedial practices to those largely deviating from the norm is also possible. Originality/value – The study is the first of its kind to apply the GRA method to expose individual student's cognitive learning difficulties in English public speaking. The grey S-C chart is novel in education literature, which can reveal individual student's learning difficulty patterns.

Grey relational analysis between Turkey’s macroeconomic indicators and domestic savings

2017 ◽  
Vol 7 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Engin Duran ◽  
Burcu Uzgur Duran ◽  
Diyar Akay ◽  
Fatih Emre Boran
Keyword(s):  
Grey Relational Analysis ◽  
Data Set ◽  
Content Type ◽  
Relational Analysis ◽  
Domestic Savings ◽  
Macroeconomic Indicators ◽  
Private Savings ◽  
Grey Relational ◽  
High Degree ◽  
The Relationship

Purpose It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators. Design/methodology/approach To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis. Findings The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings. Practical implications These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate. Originality/value There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.

The importance and the adaptation of internal resources as a competitive advantage for the internationalization of food companies

2019 ◽  
Vol 9 (3) ◽  
pp. 305-320
Author(s):  
Gessuir Pigatto ◽  
Giuliana Aparecida Santini Pigatto ◽  
Eduardo Guilherme Satolo ◽  
Amanda dos Santos Negreti
Keyword(s):  
Competitive Advantage ◽  
Design Methodology ◽  
Gray Relational Analysis ◽  
Resource Based View ◽  
Content Type ◽  
Internal Resources ◽  
Relational Analysis ◽  
Gray Correlation ◽  
Correlation System ◽  
Practical Implications

Purpose The purpose of this paper is to analyze how Brazilian food companies in the State of São Paulo determine the importance of and the need to adapt their internal resources as a competitive advantage for internationalization. Design/methodology/approach From a resource-based view (RBV), 35 different factors grouped into four categories were identified and presented to 24 companies. The data were analyzed through a gray relational analysis to establish all factors’ order of importance. Findings Factors linked to human and organizational resources present greater adaptability and allow companies competitive and sustainable advantages but have not yet been explored thoroughly. Identifying and adapting internal resources do not guarantee achieving competitive and sustainable advantages, as the access to international market is also a consequence of commercial agreements developed by countries and economic blocks. Practical implications The analysis highlights the fragility of competitiveness among the companies analyzed in exporting products with commodity characteristics, with none or little differentiation. Such products are traded mainly through trading companies, which allow the access of the same market to internal competitors and other countries. Thus, any lapse promoted by the company may be enough for it to lose its competitiveness and, hence, market space. Originality/value This paper stands out in the field of strategic management, specifically in the research on RBV, exportation and competitiveness, by making use of the theory of gray correlation system in an innovative and original way.

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