Providing consumers with a representative subset from online reviews

2017 ◽  
Vol 41 (6) ◽  
pp. 877-899 ◽  
Author(s):  
Jin Zhang ◽  
Ming Ren ◽  
Xian Xiao ◽  
Jilong Zhang
Keyword(s):  
Large Scale ◽  
User Study ◽  
Real Data ◽  
Online Reviews ◽  
Heuristic Approach ◽  
Online Information ◽  
Consumer Decision Making ◽  
High Coverage ◽  
Content Type ◽  
Representative Subset

Purpose The purpose of this paper is to find a representative subset from large-scale online reviews for consumers. The subset is significantly small in size, but covers the majority amount of information in the original reviews and contains little redundant information. Design/methodology/approach A heuristic approach named RewSel is proposed to successively select representatives until the number of representatives meets the requirement. To reveal the advantages of the approach, extensive data experiments and a user study are conducted on real data. Findings The proposed approach has the advantage over the benchmarks in terms of coverage and redundancy. People show preference to the representative subsets provided by RewSel. The proposed approach also has good scalability, and is more adaptive to big data applications. Research limitations/implications The paper contributes to the literature of review selection, by proposing a heuristic approach which achieves both high coverage and low redundancy. This study can be applied as the basis for conducting further analysis of large-scale online reviews. Practical implications The proposed approach offers a novel way to select a representative subset of online reviews to facilitate consumer decision making. It can also enhance the existing information retrieval system to provide representative information to users rather than a large amount of results. Originality/value The proposed approach finds the representative subset by adopting the concept of relative entropy and sentiment analysis methods. Compared with state-of-the-art approaches, it offers a more effective and efficient way for users to handle a large amount of online information.

The effect of emotions, eWOM quality and online review sequence on consumer intention to follow advice obtained from digital services

2020 ◽  
Vol 31 (3) ◽  
pp. 465-487 ◽  
Author(s):  
Carla Ruiz-Mafe ◽  
Enrique Bigné-Alcañiz ◽  
Rafael Currás-Pérez
Keyword(s):  
Structural Model ◽  
Online Reviews ◽  
Moderating Effect ◽  
Online Information ◽  
Bias Effect ◽  
Content Type ◽  
Digital Services ◽  
Information Cues ◽  
Cognitive Information ◽  
The Impact

PurposeThis paper analyses the interrelationships between emotions, the cognitive information cues of online reviews and intention to follow the advice obtained from digital platforms, paying special attention to the moderating effect of the sequencing of review valence.Design/methodology/approachThe data were collected from 830 Spanish Tripadvisor users. In a two-step approach, a measurement model was estimated and a structural model analysed to test the proposed hypotheses. SmartPLS 3.0 software was used. The moderating effect of sequencing of reviews is tested.FindingsThe data analysis showed a bias effect of review sequence on the impact of online information cues and emotions on intention to follow advice obtained from Tripadvisor. When the online reviews of a restaurant begin with positive commentaries, their perceived persuasiveness is a stronger driver of the pleasure and arousal elicited by online reviews than when they begin with negative reviews. On the other hand, the perceived helpfulness of online reviews only triggers arousal when the user reads negative, followed by positive, comments. The impact of pleasure on intention to follow the advice provided in an online travel community is higher with positive-negative than with negative-positive sequences.Originality/valueWhile researchers have demonstrated the benefits of customer reviews on company sales, a largely uninvestigated issue is the interplay between emotions and cognitive information cues in the processing of online reviews. This is one of the first studies to examine the moderating effect of conflicting reviews on the impact of emotions and cognitive information cues on consumer intention to follow the advice obtained from digital services.

scholarly journals Understanding collaborative tourism information searching to support online travel planning

2019 ◽  
Vol 43 (3) ◽  
pp. 369-386 ◽  
Author(s):  
Abu Shamim Mohammad Arif ◽  
Jia Tina Du
Keyword(s):  
Information Search ◽  
User Study ◽  
Ease Of Use ◽  
Online Information ◽  
Information Searching ◽  
Search System ◽  
Content Type ◽  
Travel Planning ◽  
Collaborative Search ◽  
Tourism Information

Purpose Collaborative information searching is common for people when planning their group trip. However, little research has explored how tourists collaborate during information search. Existing tourism Web portals or search engines rarely support tourists’ collaborative information search activities. Taking advantage of previous studies of collaborative tourism information search behavior, in the current paper the purpose of this paper is to propose the design of a collaborative search system collaborative tourism information search (ColTIS) to support online information search and travel planning. Design/methodology/approach ColTIS was evaluated and compared with Google Talk-embedded Tripadvisor.com through a user study involving 18 pairs of participants. The data included pre- and post-search questionnaires, web search logs and chat history. For quantitative measurement, statistical analysis was performed using SPSS; for log data and the qualitative feedback from participants, the content analysis was employed. Findings Results suggest that collaborative query formulation, division of search tasks, chatting and results sharing are important means to facilitate tourists’ collaborative search. ColTIS was found to outperform Tripadvisor significantly regarding the ease of use, collaborative support and system usefulness. Originality/value The innovation of the study lies in the development of an integrated real-time collaborative tourism information search system with unique features. These features include collaborative query reformulation, travel planner and automatic result and query sharing that assist multiple people search for holiday information together. For system designers and tourism practitioners, implications are provided.

A webometric analysis of online health information: sponsorship, platform type and link structures

2014 ◽  
Vol 38 (2) ◽  
pp. 209-231 ◽  
Author(s):  
Darja Groselj
Keyword(s):  
Health Information ◽  
Large Scale ◽  
Third Party ◽  
Business Strategies ◽  
Online Information ◽  
Content Type ◽  
Search Queries ◽  
Health Domains ◽  
Information Landscape ◽  
The Web

Purpose – This study aims to map the information landscape as it unfolds to users when they search for health topics on general search engines. Website sponsorship, platform type and linking patterns were analysed in order to advance the understanding of the provision of health information online. Design/methodology/approach – The landscape was sampled by ten very different search queries and crawled with VOSON software. Drawing on Roger's framework of information politics on the web, the landscape is described on two levels. The front-end is examined qualitatively by assessing website sponsorship and platform type. On the back-end, linking patterns are analysed using hyperlink network analysis. Findings – A vast majority of the websites have commercial and organisational sponsorship. The analysis of the platform type shows that health information is provided mainly on static homepages, informational portals and general news sites. A comparison of ten different health domains revealed substantial differences in their landscapes, related to domain-specific characteristics. Research limitations/implications – The size and properties of the web crawl were shaped by using third party software, and the generalisability of the results is limited by the selected search queries. Further research exploring how specific characteristics of different health domains shape provision of information online is suggested. Practical implications – The demonstrated method can be used by organisations to discern the characteristics of the online information landscape in which they operate and to inform their business strategies. Originality/value – The study examines health information landscapes on a large scale and makes an original contribution by comparing them across ten different health domains.

scholarly journals An applied approach to multi-criteria humanitarian supply chain planning for pandemic response

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Behnam Malmir ◽  
Christopher W. Zobel
Keyword(s):  
Large Scale ◽  
Primary Source ◽  
Real Data ◽  
Content Type ◽  
Simulation Based ◽  
Actual Growth Rate ◽  
Actual Growth ◽  
Deprivation Costs ◽  
Humanitarian Supply Chain ◽  
The Cost

PurposeWhen a large-scale outbreak such as the COVID-19 pandemic happens, organizations that are responsible for delivering relief may face a lack of both provisions and human resources. Governments are the primary source for the humanitarian supplies required during such a crisis; however, coordination with humanitarian NGOs in handling such pandemics is a vital form of public-private partnership (PPP). Aid organizations have to consider not only the total degree of demand satisfaction in such cases but also the obligation that relief goods such as medicine and foods should be distributed as equitably as possible within the affected areas (AAs).Design/methodology/approachGiven the challenges of acquiring real data associated with procuring relief items during the COVID-19 outbreak, a comprehensive simulation-based plan is used to generate 243 small, medium and large-sized problems with uncertain demand, and these problems are solved to optimality using GAMS. Finally, post-optimality analyses are conducted, and some useful managerial insights are presented.FindingsThe results imply that given a reasonable measure of deprivation costs, it can be important for managers to focus less on the logistical costs of delivering resources and more on the value associated with quickly and effectively reducing the overall suffering of the affected individuals. It is also important for managers to recognize that even though deprivation costs and transportation costs are both increasing as the time horizon increases, the actual growth rate of the deprivation costs decreases over time.Originality/valueIn this paper, a novel mathematical model is presented to minimize the total costs of delivering humanitarian aid for pandemic relief. With a focus on sustainability of operations, the model incorporates total transportation and delivery costs, the cost of utilizing the transportation fleet (transportation mode cost), and equity and deprivation costs. Taking social costs such as deprivation and equity costs into account, in addition to other important classic cost terms, enables managers to organize the best possible response when such outbreaks happen.

scholarly journals Testing the stability of “wisdom of crowds” judgments of search results over time and their similarity with the search engine rankings

2016 ◽  
Vol 68 (4) ◽  
pp. 407-427 ◽  
Author(s):  
Maayan Zhitomirsky-Geffet ◽  
Judit Bar-Ilan ◽  
Mark Levene
Keyword(s):  
Search Engine ◽  
Information Seeking ◽  
Large Scale ◽  
User Study ◽  
Wisdom Of Crowds ◽  
Point Scale ◽  
Content Type ◽  
Individual User ◽  
Search Results ◽  
Over Time

Purpose – One of the under-explored aspects in the process of user information seeking behaviour is influence of time on relevance evaluation. It has been shown in previous studies that individual users might change their assessment of search results over time. It is also known that aggregated judgements of multiple individual users can lead to correct and reliable decisions; this phenomenon is known as the “wisdom of crowds”. The purpose of this paper is to examine whether aggregated judgements will be more stable and thus more reliable over time than individual user judgements. Design/methodology/approach – In this study two simple measures are proposed to calculate the aggregated judgements of search results and compare their reliability and stability to individual user judgements. In addition, the aggregated “wisdom of crowds” judgements were used as a means to compare the differences between human assessments of search results and search engine’s rankings. A large-scale user study was conducted with 87 participants who evaluated two different queries and four diverse result sets twice, with an interval of two months. Two types of judgements were considered in this study: relevance on a four-point scale, and ranking on a ten-point scale without ties. Findings – It was found that aggregated judgements are much more stable than individual user judgements, yet they are quite different from search engine rankings. Practical implications – The proposed “wisdom of crowds”-based approach provides a reliable reference point for the evaluation of search engines. This is also important for exploring the need of personalisation and adapting search engine’s ranking over time to changes in users preferences. Originality/value – This is a first study that applies the notion of “wisdom of crowds” to examine an under-explored in the literature phenomenon of “change in time” in user evaluation of relevance.

scholarly journals Resources for Genetic and Genomic Analysis of Emerging Pathogen Acinetobacter baumannii

2015 ◽  
Vol 197 (12) ◽  
pp. 2027-2035 ◽  
Author(s):  
Larry A. Gallagher ◽  
Elizabeth Ramage ◽  
Eli J. Weiss ◽  
Matthew Radey ◽  
Hillary S. Hayden ◽  
...  
Keyword(s):  
Acinetobacter Baumannii ◽  
Large Scale ◽  
Experimental Studies ◽  
Bacterial Pathogen ◽  
Genomic Analysis ◽  
Multidrug Resistant ◽  
Health Care Facilities ◽  
High Coverage ◽  
Content Type ◽  
Genome Scale

ABSTRACTAcinetobacter baumanniiis a Gram-negative bacterial pathogen notorious for causing serious nosocomial infections that resist antibiotic therapy. Research to identify factors responsible for the pathogen's success has been limited by the resources available for genome-scale experimental studies. This report describes the development of several such resources forA. baumanniistrain AB5075, a recently characterized wound isolate that is multidrug resistant and displays robust virulence in animal models. We report the completion and annotation of the genome sequence, the construction of a comprehensive ordered transposon mutant library, the extension of high-coverage transposon mutant pool sequencing (Tn-seq) to the strain, and the identification of the genes essential for growth on nutrient-rich agar. These resources should facilitate large-scale genetic analysis of virulence, resistance, and other clinically relevant traits that makeA. baumanniia formidable public health threat.IMPORTANCEAcinetobacter baumanniiis one of six bacterial pathogens primarily responsible for antibiotic-resistant infections that have become the scourge of health care facilities worldwide. Eliminating such infections requires a deeper understanding of the factors that enable the pathogen to persist in hospital environments, establish infections, and resist antibiotics. We present a set of resources that should accelerate genome-scale genetic characterization of these traits for a reference isolate ofA. baumanniithat is highly virulent and representative of current outbreak strains.

Prospective study using archetypes and system dynamics

2019 ◽  
Vol 32 (2) ◽  
pp. 181-202
Author(s):  
Patricio Vera ◽  
Christopher Nikulin ◽  
Monica Lopez-Campos ◽  
Rosa Guadalupe G. Gonzalez Ramirez
Keyword(s):  
System Dynamics ◽  
Large Scale ◽  
Expert Knowledge ◽  
Mining Industry ◽  
Real Data ◽  
Model Management ◽  
Dynamics Simulation ◽  
Content Type ◽  
Holistic Understanding

Purpose The purpose of this paper is to propose a combination of forecasting methods that enables a holistic understanding of a future situation, given certain influencing variables by a combination of real data and expert knowledge. Design/methodology/approach The proposal combines two well-known methods: first, system archetypes that correspond to generic structures, allowing us to handle model management issues, and second, system dynamics that offers technical support on a computational level to assess different scenarios or problem solutions. Findings The case study considers the situation of the mining industry in Chile and its related variables, including four different scenarios. Based on the proposed methodology, the results indicate that: first, the price of copper is paramount for the industry and its effects are not limited to company profits; second, a long period of downfall in copper prices could halt exploration and development projects. Research limitations/implications Systemic archetypes are still a subject of research and their application in different fields of knowledge continues to increase to improve this simulation approach. Practical implications The case study illustrates the combination of a Vester matrix and initial system archetype models that are enriched using the system dynamics approach. Indeed, the case study aims to understand the consequences of different scenarios based on the problem-driven approach provided by Vester. Social implications The goal of prospective studies of large-scale and complex situations is to model the real situation to obtain solutions that may enhance social welfare. Originality/value The proposed methodology contributes to the existing literature by integrating techniques such as the Vester matrix, system archetype modelling and system dynamics simulation, all of which were proposed previously in the literature as independent techniques.

New online recommendation approach based on unbalanced linguistic label with integrated cloud

Kybernetes ◽  
2018 ◽  
Vol 47 (7) ◽  
pp. 1325-1347 ◽  
Author(s):  
Meng-Xian Wang ◽  
Jian-qiang Wang
Keyword(s):  
Recommendation System ◽  
Cloud Model ◽  
Real Data ◽  
Online Reviews ◽  
Linguistic Information ◽  
Content Type ◽  
Conversion Model ◽  
Linguistic Label ◽  
User Clustering ◽  
Value Range

Purpose Online reviews increasingly present the characteristic of bidirectional communication with the advent of Web 2.0 era and tend to be asymmetrical and individualized in linguistic information. The authors aim to develop a new linguistic conversion model that exploits the asymmetric and personalized information from online reviews to express such linguistic information. A new online recommendation approach is provided. Design/methodology/approach The necessity of new linguistic conversation model is elucidated, and a leverage factor is incorporated into the linguistic label of negative review to handle the asymmetry problems of linguistic scale. A possible value range of the leverage factor is studied. A new linguistic conversation model is accordingly established with an unbalanced linguistic label and a cloud model. The authors develop a new online recommendation approach based on several modules, such as initialization, conversion, user-clustering and recommendation models. Findings The unbalanced effect between negative and positive reviews is verified with real data and measured using indirect methods. A new online recommendation approach of electronic products is proposed and used as an illustrative example to prove the practicality, effectiveness and feasibility of the proposed approach. Research limitations/implications Due to the unavailable transaction information of customers, the limitation of this study is the effectiveness of the authors’ established recommendation system for platform or website cannot be verified. Originality/value In most existing studies, the influence of negative review is counterbalanced by positive review, and the unbalanced effect between negative and positive reviews is ignored. The negative review receives much attention from consumers and businesses. This study thus highlights the influence of negative review.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

Categorization flexibility and unconventional choices: is life an adventure?

2020 ◽  
Vol 54 (8) ◽  
pp. 1963-1986
Author(s):  
Tilottama G. Chowdhury ◽  
Feisal Murshed
Keyword(s):  
Interactive Effect ◽  
Interactive Effects ◽  
Cognitive Capacity ◽  
Purchase Behavior ◽  
Consumer Decision Making ◽  
Cross Sectional ◽  
Content Type ◽  
Cross Domain ◽  
Multiple Domains

Purpose This paper proposes that categorization flexibility, operationalized as the cognitive capacity that cross-categorizes products in multiple situational categories across multiple domains, might favorably influence a consumer’s evaluation of unconventional options. Design/methodology/approach Experimental research design is used to test the theory. An exploratory study first establishes the effect of categorization flexibility in a non-food domain. Study 1 documents the moderating role of decision domain, showing that the effect works only under low- (vs high-) consequence domain. Studies 2A and 2B further refine the notion by showing that individuals can be primed in a relatively higher categorization flexibility frame of mind. Study 3 demonstrates the interactive effect of categorization flexibility and adventure priming in a high-consequence domain. Study 4 integrates the interactive effects of decisions with low- vs high-consequence, adventure priming and categorization flexibility within a single decision domain of high consequence. Findings Consumers with higher- (vs lower-) categorization flexibility tend to opt for unconventional choices when the decision domain entails low consequences, whereas such a result does not hold under decision domain of high consequences. The categorization flexibility effects in case of low-consequence decision domain holds true even when consumers are primed to be categorization flexible. Furthermore, with additional adventure priming, consumers show an increased preference for unconventional options even under a decision domain with high consequence. Research limitations/implications This study could not examine real purchase behavior as results are based on cross-sectional, behavioral intention data. In addition, it did not examine the underlying reason for presence of cross-domain categorization flexibility index. Practical implications The results suggest that stimuli may be tailored to consumers in ways that increase the salience and the perceived attractiveness of unconventional choices. Further, data reinforce the notion of cross-categorical interrelations among different domains, which could be leveraged by marketers. Originality/value This study represents the first documentation of the potential ways by which unconventional product choice might be a function of individuals’ categorization flexibility level across different types of decision domains. The findings yield implications that are novel to both categorization and consumer decision-making literature.

Sign in / Sign up

Export Citation Format

Share Document