Search results

Comparative opinions widely exist in online reviews as a common way of expressing consumers’ ideas or preferences toward certain products. Such opinion-rich texts are key proxies for detecting product competitiveness. The purpose of this paper is to set up a model for competitiveness analysis by identifying comparative relations from online reviews for restaurants based on both pattern matching and machine learning.

The authors define the sub-category of comparative sentences according to Chinese linguistics. Classification rules are set up for each type of comparative relations through class sequence rule. To improve the accuracy of classification, a comparative entity dictionary is then introduced for further identifying comparative sentences. Finally, the authors collect reviews for restaurants from Dianping.com to conduct experiments for testing the proposed model.

The experiments show that the proposed method outperforms the baseline methods in terms of precision in identifying comparative sentences. On the basis of such comparison-rich sentences, product features and comparative relations are extracted for sentiment analysis, and sentimental score is assigned to each comparative relation to facilitate competitiveness analysis.

Only the explicit comparative relations are discussed, neglecting the implicit ones. Besides that, the study is grounded in the assumption that all features are homogeneous. In some cases, however, the weights to different aspects are not of the same importance to market.

On the basis of comparative relation mining, product features and comparative opinions are extracted for competitiveness analysis, which is of interest to businesses for finding weakness or strength of products, as well as to consumers for making better purchase decisions.

Comparative relation mining could be possibly applied in social media for identifying relations among users or products, and ranking users or products, as well as helping companies target and track competitors to enhance competitiveness.

The authors propose a research framework for restaurant competitiveness analysis by mining comparative relations from online consumer reviews. The results would be able to differentiate one restaurant from another in some aspects of interest to consumers, and reveal the changes in these differences over time.

The purpose of this paper is to apply expectation-confirmation theory (ECT) and the unified theory of acceptance and use of technology (UTAUT) to identify potential determinants of library patrons’ intention to continue using (continuance) self-issue and return systems for borrowing and returning books. The role of continuance is specifically interesting and is well-established in the literature of information systems (ISs) and marketing because continuance is considered to be the central element for the survival of ISs and of self-service technology (SST). However, the role of continuance has been neglected by researchers studying library SST adoption.

A research model integrating the expectation-confirmation model of IS continuance with UTAUT was developed and empirically validated using data obtained from a field survey involving 128 active users of a self-issue and return system at a public library in Taiwan.

Library patrons’ continuance intention was affected by their post-adoption expectation of perceived performance, effort performance and facilitating conditions as well as their satisfaction when using self-issue and return systems. Moreover, a patron satisfaction level was influenced by performance expectancy and confirmation of initial expectations, whereas confirmation had a positive effect on all post-adoption expectations.

This study broadens perspectives on SST adoption behavior in the library context by identifying some factors that influence library patrons’ continuance decisions. Furthermore, the authors verified the applicability and predictability of the theoretical integration of ECT with UTAUT in a diverse setting because the authors sought survey participants outside of the college population.

Purpose: This research investigates the effects of the coronavirus pandemic on Portuguese and Brazilian consumers’ vulnerability in contrasting age groups. It seeks to establish the relationship between fear of COVID-19 and the pandemic’s impact on customer’s vulnerability to help companies design strategies to cope with this new market context and be prepared to address these vulnerabilities in a future international health crisis.

Design/Methodology/Approach: This study employs a quantitative research method to assess the different impacts of the COVID-19 pandemic on consumer vulnerability. Based on Portuguese and Brazilian residents’ surveys, an age/country-segmented cross-cultural multi-group analysis was performed to understand the differences in vulnerability.

Findings: Outcomes proved how the pandemic aggravates distinctively the vulnerability dimensions of consumers living in Portugal and Brazil. Besides, results highlight significant differences in consumers’ vulnerability during the pandemic given their age group. A positive correlation between age and fear of COVID-19 was also verified.

Value: Results were obtained based on consumers’ perceptions and scores rather than postulated behaviors. The findings highlight the need for health prevention measures to avoid neglecting existing vulnerable groups, whilst verifying how COVID-19 has managed to proliferate consumers’ vulnerability. Suggestions are drawn for both firms and governments based on obtained results and existing literature. Exemplar business strategies to avoid these vulnerabilities are put forward and discussed. The potential business advantages of firms shaping their activity according to their customers’ current vulnerabilities, during international pandemics, are also pointed.

The purpose of this paper is to investigate an online monitoring strategy that incorporates fiber Bragg gratings (FBGs) for deformation displacement detection, with the background that slope deformation monitoring is crucial to engineering safety supervision and disaster prevention.

A “beam element” method has been proposed, introduced and experimentally verified in detail. The deformation displacement along a flexible bar can be obtained based on this method, using the distributed strain detected by the FBGs embedded in the bar. A novel sensor structure containing inclinometer casings and a series of connected flexible pipes with FBGs embedded has been proposed. Based on the features of this structure, two FBG deformation sensors have been manufactured and installed into a slope. A matched monitoring station which permits real-time supervision, warning and remote access across the Internet was established and operated.

Displacement data from September 2013 to August 2014 are obtained, which is basically consistent with the practical situation.

The FBG deformation sensors demonstrated a robust and reliable measurement performance, which is promising for real-time disaster warning in slope engineering.

Centrifugal model tests can accelerate the characterization of landslides and demonstrate the form of slope failure, which is an important measure to research its instability mechanisms. Simply observing the slope landslide before and after a centrifugal model test cannot reveal the processes involved in real-time deformation. Electromagnetic sensors have severed as an existing method for real-time measurement, however, this approach has significant challenges, including poor signal quality, interference, and complex implementation and wiring schemes. This paper aims to overcome the shortcomings of the existing measurement methods.

This work uses the advantages of fiber Bragg grating (FBG) sensors with their small form-factor and potential for series multiplexing in a single fiber to demonstrate a monitoring strategy for model centrifugal tests. A slope surface deformation displacement sensor, FBG anchor sensor and FBG anti-slide piling sensor have been designed. These sensors are installed in the slope models, while centrifugal acceleration tests under 100 g are carried out.

FBG sensors obtain three types of deformation information, demonstrating the feasibility and validity of this measurement strategy.

The experimental results provide important details about instability mechanisms of a slope, which has great significance in research on slope model monitoring techniques and slope stability.

While past research has explored how opting-out enables mothers to break free from masculinist organizational cultures, less attention has been given to how they resist disciplinary power that constitutes and governs their subjectivities. This paper aims to add to the discussion of opting-out as a site of power and resistance by proposing the concept of “constructive resistance” as a productive vantage point for investigating opted-out mothers' subversive practices of self-making.

This Malaysian case study brings together the notion of constructive resistance, critical narrative analysis and APPRAISAL theory to examine the reflective stories of eighteen mothers who exited formal employment. These accounts were collected through an open-ended questionnaire and semi-structured email interviews.

The mothers in the sample tend to construct themselves in two main ways, as (1) valuable mothers (capable, tireless, caring mothers who are key figures in their children's lives) and (2) competent professionals. These subjectivities are parasitic on gendered and neoliberal ideals but allow the mothers to undermine neoliberal capitalist work arrangements that were incongruent with their personal values and adversely impacted their well-being, as well as refuse organizational narratives that positioned them as “failed” workers.

Whereas power is primarily seen in previous opting-out scholarship as centralized and constraining, this case study illustrates how the lens of constructive resistance can be beneficial for examining opted-out mothers' struggles against a less direct form of power that governs through the production of truths and subjectivities.

This study aims to explore the dimensions of perceived consumption vulnerability (PCV) for the elderly citizens (EC) in India and its consequences. Consumer vulnerability is a recent and important construct for marketers and policymakers to understand the consumption behavior of the EC.

To achieve the study objectives, the authors conducted 50 in-depth interviews and six focus group discussions of ECs in two large cities in India. The authors used grounded theory methodology to understand the PCV construct.

The findings suggest a five-dimensional formative PCV construct with the dimensions being Physical, Financial, Social, Technological and Service Vulnerability contributing to PCV. The findings also suggest a relationship between PCV and consumption variables such as search cost, choice evaluation, consumption and overall satisfaction.

The major contribution of the present study is the exploration of the PCV construct for the EC and its dimensions. The propositions developed in the study could be tested in future studies using a quantitative approach.

The findings call for compassion from the marketers while dealing with the ECs and a separate service strategy that addresses the specific needs of the ECs.

The findings call for public policy action to protect the consumption rights of the ECs to reduce their consumption vulnerability.

The present study is a novel attempt to explore the PCV construct and its role in defining consumer behavior of the ECs.

With the explosive growth of information available on the World Wide Web, it has become much more difficult to access relevant information from the Web. One possible approach to solve this problem is web personalization. In this paper, we propose a novel WUL (Web Usage Lattice) based mining approach for mining association access pattern rules for personalized web recommendations. The proposed approach aims to mine a reduced set of effective association pattern rules for enhancing the online performance of web recommendations. We have incorporated the proposed approach into a personalized web recommender system known as AWARS. The performance of the proposed approach is evaluated based on the efficiency and the quality. In the efficiency evaluation, we measure the number of generated rules and the runtime for online recommendations. In the quality evaluation, we measure the quality of the recommendation service based on precision, satisfactory and applicability. This paper will discuss the proposed WUL‐based mining approach, and give the performance of the proposed approach in comparison with the Apriori‐based algorithms.

Computer based systems have great potential for delivering learning material. However, problems are encountered, such as: difficulty of Learning resource sharing, high redundancy of learning material, and deficiecy of the course brief. In order to solve these problems, this paper aims to propose an automatic inquiring system for learning materials which, utilize the data‐sharing and fast searching properties of the Lightweight Directory Access Protocol (LDAP) and JAVA Architecture for XML Binding (JAXB).

The paper describes an application to utilize the techniques of LDAP and JAXB to reduce the load of search engines and the complexity of content parsing. Additionally, through analyzing the logs of learners' learning behaviors, the likely keywords and the association among the learning course contents is ascertained. The integration of metadata of the learning materials in different platforms and maintenance in the LDAP server is specified.

As a general search engine, learners can search contents by using multiple keywords concurrently. The system also allows learners to query by content creator, topic, content body and keywords to narrow the scope of materials.

Teachers can use this system more effectively in their education process to help them collect, process, digest and analyze information.