Search results

This study aims to analyse online customer experience in the hospitality industry through dynamic topic modelling (DTM) and net promoter score (NPS). A novel model that was used for collecting, pre-processing and analysing online reviews was proposed to understand the hidden information in the corpus and gain customer experience.

A corpus with 259,470 customer comments in English was collected. The researchers experimented and selected the best K parameter (number of topics) by perplexity and coherence score measurements as the input parameter for the model. Finally, the team experimented on the corpus using the Latent Dirichlet allocation (LDA) model and DTM with K coefficient to explore latent topics and trends of topics in the corpus over time.

The results of the topic model show hidden topics with the top high-probability keywords that are concerned with customers and the trends of topics over time. In addition, this study also calculated and analysed the NPS from customer rating scores and presented it on an overview dashboard.

The data used in the experiment are only a part of all user comments; therefore, it may not reflect all of the current customer experience.

The management and business development of companies in the hotel industry can also benefit from the empirical findings from the topic model and NPS analytics, which will support decision-making to help businesses improve products and services, increase existing customer satisfaction and draw in new customers.

This study differs from previous works in that it attempts to fill a gap in research focused on online customer experience in the hospitality industry and uses text analytics and NPS to reach this goal.

本研究旨在通过动态主题建模和净推荐值分析酒店业的在线客户体验。 提出了一种用于收集、预处理和分析在线评论的新模型, 以了解语料库中的隐藏信息并获得客户体验。

收集了一个包含 259,470 条英文客户评论的语料库。 研究人员通过 Perplexity 和 Coherence Score 测量结果进行了实验, 并选择了最佳的 K 参数（主题数量）作为模型的输入参数。 最后, 团队使用 Latent Dirichlet allocation (LDA) 模型和具有 K 系数的 Dynamic Topic Model (DTM) 在语料库上进行实验, 以探索语料库中的潜在主题和主题随时间变化的趋势。

主题模型的结果显示了隐藏的主题, 其中包含与客户相关的顶级高概率关键字以及主题随时间的变化趋势。 此外, 该研究还根据客户评分计算和分析净推荐值 (NPS), 并将其显示在概览仪表板上。

实验中使用的数据只是所有用户评论的一部分; 因此, 它可能无法反映所有当前的客户体验。

酒店业公司的管理和业务发展也可以受益于主题模型和 NPS 分析的实证结果, 这将支持决策制定, 帮助企业改进产品和服务, 提高现有客户满意度, 并吸引新客户 .

本研究不同于以往的研究, 因为它试图填补以酒店业在线客户体验为重点的研究空白, 并使用文本分析和 NPS 来实现这一目标。

This study aims to use the voice of the customer (VoC) strategy to collect user-generated content (UGC) compare customer expectations with reality, make the necessary improvements for the business and create personalized strategies for each customer to maximize revenue, focus on hospitality industry in Vietnam market.

This study proposes a synthesis of techniques for a deep understanding of the VoC based on online reviews in the hospitality industry. First, 409,054 comments were collected from websites in the hospitality sector. Second, the data will be organized, stored, cleaned, analyzed and evaluated. Next, research using business intelligence (BI) solutions integrating three models, including net promoter score (NPS), graph model and latent Dirichlet allocation (LDA), based on natural language processing (NLP) technique, experiment on Vietnamese and English data to explore the multidimensional voice of customer’s row. Finally, a dashboard system will be implemented to visualize analysis results and recommendations on marketing strategies to improve product and service quality.

Experimental results allow analysts and managers to “listen to the customer’s voice” accurately and effectively, identify relationships between entities, topics of discussion in favor of positive and negative trends.

The novelty in this study is the integration of three models, including NPS, graph model and LDA. These models are combined based on the BI solution and NLP technique. The study also conducted experiments on both Vietnamese and English languages, which ensures more effective practical application.

This study aims to investigate countries without national property insurance and see how experience affects behavior toward higher-risk flood prone property.

Using a unique data set that captures the flood experiences of homeowners that search for new housing, the authors examine the premiums or discounts of such experience on homes at risk. The authors use hedonic property modeling to estimate the effects of experience on values.

The authors find that such experiences play a strong role in convincing buyers of the real risks imposed by climate change and sea level rise and the authors expect these demand-side behavioral changes to persist. This finding is unlike more developed markets where insurance may be subsidized and negative effects on value dissipate within a few years.

The world is starting to pay more attention to climate risk and the results in developed countries have been biased by the extensive insurance provided by the government or emergency funding.

Providing market transparency on climate risks will result in permanent market effects, if not otherwise subsidized.

The governments should encourage market disclosure.

No one has ever had a data set like this before where the authors get to observe the behavior of those already experiencing property losses from flooding.

The purpose of the research is to investigate whether corporate social responsibility awareness (pCSR), environmental concerns (EC) and consumer environmental knowledge (CK) will have an impact on sustainable purchase intention (SPI). Furthermore, this paper also contributes to surveying the mediating impact of consumer attitudes (CAs) between intention and the three factors mentioned above.

SmartPLS (version 4.0) structural equation modeling (SEM) and quantitative methods were used to analyze 457 responses from consumers. The survey sample consisted of individuals between the ages of 18 and 34, with a male-to-female ratio of 70 to 30. The study aims to examine and put into practice new directions for manufacturing firms in the fields of fashion, food and consumer products. At the same time, provide more convincing evidence about the use of these fields in the research.

The study showed a favorable link between pCSR, EC, CK and SPI through the proposed hypotheses. The research additionally showed that CAs mediate between the aforementioned variables.

The important and distinctive results of this study encourage both consumers and enterprises to make changes in their perceptions of society. Consumers should gradually change their daily lifestyle by consuming more sustainable products. As a result, this outcome will provide the impetus for manufacturing businesses to alter their operational procedures in order to support the shift from the production of products to more friendly processes, with the help of all levels of management within the business.

The problem of image retrieval and image description exists in various fields. In this paper, a model of content-based image retrieval and image content extraction based on the KD-Tree structure was proposed.

A Random Forest structure was built to classify the objects on each image on the basis of the balanced multibranch KD-Tree structure. From that purpose, a KD-Tree structure was generated by the Random Forest to retrieve a set of similar images for an input image. A KD-Tree structure is applied to determine a relationship word at leaves to extract the relationship between objects on an input image. An input image content is described based on class names and relationships between objects.

A model of image retrieval and image content extraction was proposed based on the proposed theoretical basis; simultaneously, the experiment was built on multi-object image datasets including Microsoft COCO and Flickr with an average image retrieval precision of 0.9028 and 0.9163, respectively. The experimental results were compared with those of other works on the same image dataset to demonstrate the effectiveness of the proposed method.

A balanced multibranch KD-Tree structure was built to apply to relationship classification on the basis of the original KD-Tree structure. Then, KD-Tree Random Forest was built to improve the classifier performance and retrieve a set of similar images for an input image. Concurrently, the image content was described in the process of combining class names and relationships between objects.

The purpose of this paper is to explore the influence of culture on the sense of self-efficacy in teaching English as a Foreign Language of a group of university teachers in Vietnam. Research exploring the relationship between culture and self-efficacy is extremely rare despite the acknowledged importance of culture in the formation of self-efficacy beliefs.

This study took the form of qualitative research with diverse, data collection instruments: individual interviews, focus group discussions, observations and journaling.

Findings indicate that certain features of the Vietnamese cultural context impacted on the way the study teachers constructed their sense of self-efficacy. Specifically, under the influence of a Vietnamese sense of belonging, the study teachers tended to rely more on efficacy-building information from other people rather than from themselves. The perception of inequality in power may have heightened negative emotional arousal, thus contributing to a negative sense of self-efficacy among the teachers. The Vietnamese concept of face and the high status of teachers in the social hierarchy in part mediated teachers’ sense of self-efficacy.

The perceived burden of performing both parenting and teaching roles and responsibilities may have diminished the self-efficacy in teaching of female teachers.

The contribution and implications of the study are discussed.

This study aims to the development of the scale of supply chain performance measures (SCPMs), food supply chain resilience (FSCS) and sustainable corporate performance (SCP) in small- and medium-sized enterprises (SMEs) in an emerging market. Based on this purpose, the study examines the relationships between SCPMs and SCP by exploring the mediating role of FSCS in emerging markets.

Based on a comprehensive literature review on the SCPMs, FSCS and SCP, the author evaluates the nexus of these constructs on disruptions during the COVID-19 pandemic emergency in an emerging market. The article follows a quantitative approach. A total of 567 valid responses from managers at senior and middle levels were received and used for data analysis. The Smart PLS version 3.3.2 was employed to analyse Structural Equation Modelling (SEM) to investigate the relationships between constructs and latent variables.

This study provides some theoretical contributions to expand the extant literature on the domain of SCPMs. First, the findings determine that multidimensional measures of flexibility, diversity, agility, inventory efficiency, redundancy and robustness are appropriate for measuring food SC performance in disruptions during the COVID-19 emergency. Besides, this study enriches the existing literature on SC disruption by providing extensive empirical evidence on SCPMs in disruptions during the COVID-19 emergency. Finally, this research provides an integrated empirical model that explores the link between the identified food SCPMs to FSCS and SCP.

The contributions may be of interest to business practitioners, business leaders and academics. In addition, this study provides empirical evidence to demonstrate that food SC performance, as measured by these measures, is strongly related to the firm's food supply chain resilience. This is the novel contribution of this study to the current literature on food SC management. Furthermore, this study provides further empirical evidence demonstrating the partial mediating role of the firm's food supply chain resilience in the nexus between food SC performance and SCP. The unique contribution of this study is an extension of the body of knowledge of SC management literature from a comprehensive approach by providing a proven set of performance measures of SC management to which it can drive SC resilience and SCP for food manufacturing SMEs in an emerging economy that hardly found in the current literature.

The purpose of this paper is to investigate the input- and output-specific technical inefficiency of Vietnamese prawn-rice rotational crops (PRRC) and to identify the impacts of the socio-economic characteristics of farmers and farms on these technical inefficiencies.

This study first used a Russell-type (input-output) directional distance function to estimate the input- and output-specific technical inefficiency. Second, it applied a bootstrap truncated regression to analyze the factors influencing these technical inefficiencies. Data were gathered through a survey among 94 farmers, from Ben Tre and Kien Giang provinces, the two popular PRRC areas in the Mekong Delta.

Results show that Vietnamese PRRC farmers could reduce the water surface area by 3%, the use of seedlings by 15%, labor by 16%, fertilizers by 26%, and the use of others by 24%, while simultaneously increasing the revenue of farming system by 57% relative to the variable returns to scale (VRS) frontier. Farmers with more years of experience are generally better in managing the use of seedlings and in improvement of revenue. Farmers in Kien Giang province are more efficient in achieving revenue of the PRRC farming system than farmers in Ben Tre province.

Outcomes of this study are useful to identify strategies in minimizing the use of inputs while simultaneously maximizing PRRC production.

This paper relates to the comparison of two mostly different ecological zones, being the dominant production areas of PRRC, in which, Kien Giang represents the western part, while Ben Tre is in the eastern part of the Vietnam’s Mekong Delta. The findings not only expand the current understanding but also suggest various meaningful research questions regarding the development of Vietnamese PRRC under the impacts of climate change. The study also contributes to the literature on examining the input- and output-specific technical inefficiencies and influencing factors.

This study aims to examine the relationship between human resource development (HRD) and the interaction between corporate social responsibility (CSR) and marketing capabilities in small and medium enterprises (SMEs) in the food industry.

This research uses the extended regression model on a sample of 2,649 food SMEs in Vietnam.

This research found that CSR and marketing strategies positively influence HRD; the interaction of CSR and marketing capabilities has a negative effect on HRD; the endogenous role of network capabilities on the effects of CSR and marketing capabilities on HRD.

This research helps food companies use their resources in allocating resources for CSR and conduct marketing reasonably and effectively. This study highlights that the impact of CSR and marketing on HRD is dominated by endogenous networking.

This study aims to develop a competency model for the Vietnamese workforce in the era of Industry 4.0.

A combination of an online survey and a Delphi study was conducted to identify a set of skills, abilities, knowledge and personalities that are critical for effective performance in the future workplace.

A set of 26 competencies was identified. Similar to previous findings in the context of developed countries, the set centres around a group of competencies commonly called “21st century competencies”. It also includes characteristics unique to a developing nation.

The proposed framework of competencies may not cover all human capabilities necessitated by the workplace and may include items with overlapping definitions. The study only represents the view of the business community, and its survey sample was limited in size and location. The impact of COVID-19 on the competency model was not explicitly covered during the study.

The competency model could serve as a basis for the educator to reform curricula, the policy maker to devise policies and the employer to develop training programmes. It can be used as a reference for other nations at similarly-developmental level.

The present study is among a few empirical studies regarding a model for Industry 4.0 competencies in the context of low middle-income countries and probably provides one of the first Industry 4.0 competency models for Vietnam. It also provides a novel framework for identifying and analyzing competencies.