R. Venkatesakumar, Sudhakar Vijayakumar, S. Riasudeen, S. Madhavan and B. Rajeswari
The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews…
Abstract
Purpose
The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers.
Design/methodology/approach
Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms.
Findings
The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews.
Research limitations/implications
The authors did not analyse data across demographic details because of access restriction policies of the websites.
Practical implications
Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously.
Social implications
This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers.
Originality/value
This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.
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B. Rajeswari, S. Madhavan, Ramakrishnan Venkatesakumar and S. Riasudeen
This study aims to compare online review characteristics, review length and review sentiment score between “organic” and “regular” food products. In addition, variations in the…
Abstract
Purpose
This study aims to compare online review characteristics, review length and review sentiment score between “organic” and “regular” food products. In addition, variations in the consumer sentiment scores across the review lengths are studied.
Design/methodology/approach
This study fits into the descriptive research design. From Amazon’s website, the consumer product reviews are scrapped. Using the text analytical package “sentiment” in R-Studio, we computed the sentiment scores and counted the number of words in each review. The mean sentiment scores and mean review length are compared for regular and organic products using one-way ANOVA. Sentiment score variation across review length and product class is studied through factorial ANOVA. Sample reviews of ghee and honey are used to test the hypotheses.
Findings
The review length shows a significant difference between the regular and organic products. The mean number of words in the regular products reviews is significantly lower than the mean number of words in the organic product reviews. The regular products’ mean sentiment score is significantly lower than the mean sentiment score of organic products. The mean sentiment scores are not consistent between ghee and honey. Sentiment scores are better for organic honey and regular ghee products. For regular ghee products, longer reviews result in lower sentiment scores. For regular and organic versions of honey, longer reviews are associated with better sentiment scores.
Research limitations/implications
This study did not include the helpfulness of a review and the demographic data of the reviewers.
Practical implications
Sentiment scores’ variations across the regular and organic and product categories such as ghee and honey give a comprehensive feedback to the firms. It also indirectly communicates a brand’s evaluation by the consumers and the performance feedback for an upward extension like the organic category.
Social implications
Studies on organic category give feedback for environment-friendly products and consumer attitude shift towards safer products.
Originality/value
Very limited studies have reported the upward line extensions. The authors study the upward line extension organic and associated sentiment scores variation. The role of review length and its systematic influence on the sentiment scores, variations in the review due to the product nature (organic/regular) are unique contributions of this study.
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Manjula T., Rajeswari R. and Praveenkumar T.R.
The purpose of this paper is to assess the application of graph coloring and domination to solve the airline-scheduling problem. Graph coloring and domination in graphs have…
Abstract
Purpose
The purpose of this paper is to assess the application of graph coloring and domination to solve the airline-scheduling problem. Graph coloring and domination in graphs have plenty of applications in computer, communication, biological, social, air traffic flow network and airline scheduling.
Design/methodology/approach
The process of merging the concept of graph node coloring and domination is called the dominator coloring or the χ_d coloring of a graph, which is defined as a proper coloring of nodes in which each node of the graph dominates all nodes of at least one-color class.
Findings
The smallest number of colors used in dominator coloring of a graph is called the dominator coloring number of the graph. The dominator coloring of line graph, central graph, middle graph and total graph of some generalized Petersen graph P_(n ,1) is obtained and the relation between them is established.
Originality/value
The dominator coloring number of certain graph is obtained and the association between the dominator coloring number and domination number of it is established in this paper.
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P. G. S. A. Jayarathne, Narayanage Jayantha Dewasiri and K. S. S. N. Karunarathne
Owing to the significance of a healthy lifestyle, we investigate the antecedents of the healthy lifestyle of young consumers in Sri Lanka. 658 structured questionnaires were…
Abstract
Owing to the significance of a healthy lifestyle, we investigate the antecedents of the healthy lifestyle of young consumers in Sri Lanka. 658 structured questionnaires were collected from young consumers in Sri Lanka as part of the survey procedure. The judgmental sampling method is used to choose the respondents. The analysis makes use of both descriptive and inferential statistics. The findings disclose a high degree of healthy lifestyle among young consumers in Sri Lanka. Further findings revealed that health consciousness, collective esteem, and neighborhood environment are the antecedents for a healthy lifestyle. As young consumers are more concerned about a healthy lifestyle, managers in certain industries such as food and beverages, hotels, and restaurants should adopt their products and services in line with a healthy lifestyle.
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Md Shamim Hossain and Mst Farjana Rahman
The main goal of this study is to employ unsupervised (lexicon-based) learning approaches to identify readers' emotional dimensions and thumbs-up empathy reactions to reviews of…
Abstract
Purpose
The main goal of this study is to employ unsupervised (lexicon-based) learning approaches to identify readers' emotional dimensions and thumbs-up empathy reactions to reviews of online travel agency apps based on appraisal and stimulus–organism–response (SOR) theories.
Design/methodology/approach
Using the Google Play Scraper, we gathered a total of 402,431 reviews from the Google Play Store for two travel agency apps, Tripadvisor and Booking.com. Following the filtering and cleaning of user reviews, we used lexicon-based unsupervised machine learning algorithms to investigate the associations between various emotional dimensions of reviews and review readers' thumbs-up reactions.
Findings
The study's findings reveal that the sentiment of different sorts of reviews has a substantial influence on review readers' emotional experiences, causing them to give the app a thumbs up review. Furthermore, readers' thumbs-up responses to the text reviews differed depending on the eight emotional aspects of the reviews.
Practical implications
The results of this research can be applied in the development of online travel agency apps. The findings suggest that app developers can enhance users' emotional experiences by considering the sentiment and emotional aspects of reviews in their design and implementation. Additionally, the results can be used by travel agencies to improve their online reputation and attract more customers by providing a positive user experience.
Social implications
The findings of this research have the potential to have a significant impact on society by providing insights into the emotional experiences of users when they engage with online travel agency apps. The study highlights the importance of considering the emotional aspect of user reviews, which can help app developers to create more user-friendly and empathetic products.
Originality/value
The current study is the first to evaluate the impact of users' thumbs-up empathetic reactions on user evaluations of online travel agency applications using unsupervised (lexicon-based) learning methodologies.
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Emre Yaşar, Mahmut Demir and Turgay Taşdemir
This study aims to examine consumers' purchasing and consumption behavior regarding big data embedded in packaged food post-Covid-19. The second purpose is to determine whether…
Abstract
Purpose
This study aims to examine consumers' purchasing and consumption behavior regarding big data embedded in packaged food post-Covid-19. The second purpose is to determine whether consumer purchasing behavior varies depending on the variety and volume of big data on food packages.
Design/methodology/approach
Semi-structured interviews were conducted to investigate consumer sentiment regarding big embedded data in packaged foods during purchasing. Based on samples from packaged foods sold in international chain stores, interview data collected from 24 participants were subjected to systematic analytical procedures.
Findings
The results revealed that before Covid-19, consumers had positive thoughts about the expiration date, brand, and product contents but did not care much about other data. At the same time, post-Covid-19, there were changes in their attitudes and behaviors on this issue. Post-Covid-19, it has been observed that consumers have positive attitudes and behaviors toward human health and food safety issues regarding unprocessed big data in packaged foods.
Originality/value
This study provides a different perspective on consumer purchasing behavior through big data on packaged foods post-Covid-19. Embedded information in packaged foods provides important data regarding consumer purchasing behavior. As a powerful source of consumer sentiment, this data also provides a reference for consumer purchasing decisions.
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An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors…
Abstract
Purpose
An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.
Design/methodology/approach
The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.
Findings
The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).
Originality/value
The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.
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Danish Hussain, Arham Adnan and Maaz Hasan Khan
The study attempted to gauge the relative effectiveness of celebrity and product image match-up in comparison to non-celebrity attractive endorsers for two distinct high…
Abstract
Purpose
The study attempted to gauge the relative effectiveness of celebrity and product image match-up in comparison to non-celebrity attractive endorsers for two distinct high involvement situations. Also, due to the expected demographic diversity among target consumers, the study aimed at assessing the impact of respondent's age and gender on the effectiveness of image match-up.
Design/methodology/approach
Building on the three-order hierarchy model, two experiments were conducted (utilising celebrity and non-celebrity endorsers) for two high involvement hierarchies, i.e. standard learning and dissonance/attribution. Through fictitious print advertisement, the experiments assessed the effectiveness of the match-up in terms of consumer attitudes towards advertisement and brand and intentions to purchase.
Findings
The match-up consistently and significantly outperformed non-celebrity attractive endorser in case of standard learning hierarchy. The same conclusion was not established for dissonance/attribution hierarchy due to the lack of significant results. The findings also suggest that the match-up subdues the impact of consumer's gender and age on consumer attitudes only in case of standard learning hierarchy.
Research limitations/implications
The study provides interesting theoretical implication by challenging a widely held postulation about the applicability of celebrity and product match-up under high involvement.
Practical implications
The research provides the practitioners with a better understanding of important issues, mainly, whether to use a celebrity endorser and selecting the right celebrity, especially if high involvement is expected.
Originality/value
Previous research concerning celebrity endorsements has largely considered consumer involvement as unitary, i.e. either high or low. However, the multifaceted aspect of consumer involvement is well established in the field of consumer psychology. The present research, therefore, is a pioneering attempt as it studies the effectiveness of match-up for two distinct high involvement situations. Moreover, unlike the majority of previous studies that have focused on the performance of “celebrity match” versus “celebrity mismatch”, the impact of match-up was studied in comparison to a non-celebrity attractive endorser.
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Muhammad Hafeez, Ida Yasin, Dahlia Zawawi, Shoirahon Odilova and Hussein Ahmad Bataineh
This study aims to investigate the effect of organizational ambidexterity (OA) and organizational green culture (OGC) on corporate sustainability (CS) while incorporating the…
Abstract
Purpose
This study aims to investigate the effect of organizational ambidexterity (OA) and organizational green culture (OGC) on corporate sustainability (CS) while incorporating the mediating role of green innovation (GI) to provide a detailed insight into CS. The study also presents a research framework based on the Organizational Ambidexterity theory and Natural Resource-based view to explain the factors contributing to CS.
Design/methodology/approach
Using stratified sampling, the study collected data through survey-based empirical research from 307 textile companies registered with the Securities and Exchange Commission of Pakistan (SECP) or the All-Pakistan Textile Mills Association (APTMA). The collected data were analysed using path analysis, mediation analysis and moderation analysis through smart PLS-SEM version 4.0 to assess the composition and causal association of factors.
Findings
The study found a significant relationship between OA and OGC with CS. Furthermore, the study revealed that green innovation partially mediates the relationship between OGC and CS. The proposed research framework can be valuable for promoting and recommending actions to enhance CS.
Research limitations/implications
The study on CS in the textile sector of Pakistan has limitations such as a narrow focus, cross-sectional design and reliance on self-reported data. Future research should explore additional factors, conduct longitudinal research, investigate contextual factors, scrutinize specific green innovation practices and broaden the scope of the study to include SMEs and other textile organizations.
Practical implications
The research framework can help senior executives to foster CS by promoting OGC, OA and GI. Practitioners and academicians can also utilize or further investigate the proposed framework for validation and to foster CS.
Originality/value
This study fills gaps in the existing literature by investigating the mediating effect of GI between OGC and CS. The proposed research framework provides a comprehensive understanding of the factors contributing to CS based on the Organizational Ambidexterity theory and Natural Resource-based view.
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Eugine Tafadzwa Maziriri, Brighton Nyagadza, Brian Mabuyana, Tarisai Fritz Rukuni and Miston Mapuranga
This paper aims to examine how health consciousness, perceived nutrition of cereals, hedonic eating values and utilitarian eating values would influence consumers’ attitudes…
Abstract
Purpose
This paper aims to examine how health consciousness, perceived nutrition of cereals, hedonic eating values and utilitarian eating values would influence consumers’ attitudes towards cereal consumption, willingness to pay for cereals, actual consumption of cereal products, cereal product consumption satisfaction and continuance of cereal consumption.
Design/methodology/approach
The research embraced a quantitative approach. The examination was completed in the Eastern Cape province of South Africa (SA). A structured questionnaire was used to collect data from 380 Generation Z consumers of cereal products. Structural equation modelling analysis was used using the smart partial least squares software to test the hypothesized model.
Findings
The results uncovered that the study variables were significantly associated, and surprisingly, the relationship between hedonic eating values and attitudes towards cereal consumption was found to be insignificant. It was also found that attitudes toward cereal consumption positively and significantly mediated the relationship between health consciousness and willingness to pay for cereals, perceived cereal nutrition and willingness to pay for cereals, hedonic eating values and willingness to pay for cereals and utilitarian eating values and willingness to pay for cereals.
Originality/value
This research adds new, fresh knowledge to the established body of knowledge on cereal consumption behaviour. This area has had little research attention in developing African countries like SA.