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Article
Publication date: 31 August 2021

Peng Luo, Eric W.T. Ngai, Yongli Li and Xin Tian

This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.

Abstract

Purpose

This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.

Design/methodology/approach

The empirical data were from an online store for the period between August 14, 2015 and May 15, 2016. The data consisted of consumer visit behavior and online store sales performance. Vector autoregression with an exogenous variables model was adopted to investigate the dynamic relationships.

Findings

The empirical results show significant relationships between visit behavior metrics (number of visitors, average number of visits per visitor and average length of each visit) in the two channels and online store sales performance. The number of visitors through the PC and mobile channels strongly and positively affects online store sales performance both in the short term and in the longer term. Moreover, the number of visitors in the PC channel has the strongest influence on sales performance metrics, followed by the number of visitors and the average number of visits in the mobile channel. The PC channel's visit behavior metrics explain a larger proportion of the sales performance variance than that in the mobile channel.

Originality/value

The previous literature on consumer behavior in multichannel marketing mainly focuses on channel selection or migration, and examines the different factors affecting channel choice behavior. Little is known about the impacts of visit behavior in the multiple channels. This study adopts the heuristic-systematic information processing theory to unveil the impacts of visit behavior metrics in the PC and mobile channels on online store sales performance.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

Keywords

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Article
Publication date: 26 September 2018

Wu He, Weidong Zhang, Xin Tian, Ran Tao and Vasudeva Akula

Customer knowledge from social media can become an important organizational asset. The purpose of this paper is to identify useful customer knowledge including knowledge…

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1922

Abstract

Purpose

Customer knowledge from social media can become an important organizational asset. The purpose of this paper is to identify useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers from social media data and facilitate social media-based customer knowledge management.

Design/methodology/approach

The authors conducted a case study to analyze people’s online discussion on Twitter regarding laptop brands and manufacturers. After collecting relevant tweets using Twitter search APIs, the authors applied statistical analysis, text mining and sentiment analysis techniques to analyze the social media data set and visualize relevant insights and patterns in order to identify customer knowledge.

Findings

The paper identifies useful insights and knowledge from customers and knowledge about customers from social media data. Furthermore, the paper shows how the authors can use knowledge from customers and knowledge about customers to help companies develop knowledge for customers.

Originality/value

This is an original social media analytics study that discusses how to transform large-scale social media data into useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers.

Details

Journal of Enterprise Information Management, vol. 32 no. 1
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 28 May 2021

Xin Tian, Wu He and Feng-Kwei Wang

In recent years, social media crises occurred more and more often, which negatively affect the reputations of individuals, businesses and communities. During each crisis…

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180

Abstract

Purpose

In recent years, social media crises occurred more and more often, which negatively affect the reputations of individuals, businesses and communities. During each crisis, numerous users either participated in online discussion or widely spread crisis-related information to their friends and followers on social media. By applying sentiment analysis to study a social media crisis of airline carriers, the purpose of this research is to help companies take measure against social media crises.

Design/methodology/approach

This study used sentiment analytics to examine a social media crisis related to airline carriers. The arousal, valence, negative, positive and eight emotional sentiments were applied to analyze social media data collected from Twitter.

Findings

This research study found that social media sentiment analysis is useful to monitor public reaction after a social media crisis arises. The sentiment results are able to reflect the development of social media crises quite well. Proper and timely response strategies to a crisis can mitigate the crisis through effective communication with the customers and the public.

Originality/value

This study used the Affective Norms of English Words (ANEW) dictionary to classify the words in social media data and assigned the words with two elements to measure the emotions: valence and arousal. The intensity of the sentiment determines the public reaction to a social media crisis. An opinion-oriented information system is proposed as a solution for resolving a social media crisis in the paper.

Details

Data Technologies and Applications, vol. 56 no. 1
Type: Research Article
ISSN: 2514-9288

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Article
Publication date: 9 October 2017

Mengyan Dai, Wu He, Xin Tian, Ashley Giraldi and Feng Gu

American police departments are beginning to implement social media as a strategy to engage the surrounding communities through various methods, including Facebook and…

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3190

Abstract

Purpose

American police departments are beginning to implement social media as a strategy to engage the surrounding communities through various methods, including Facebook and Twitter. The purpose of this paper is to examine the varieties in the use of Facebook and Twitter by local police departments.

Design/methodology/approach

This study collected all data between October 1, 2013 and March 31, 2014 from Facebook and Twitter accounts of seven city police departments in the Hampton Roads area of Virginia. These agencies resemble many police departments in the USA, and in total serve a diverse population of approximately 1,435,000. Content analysis and statistical tests are conducted.

Findings

Results show that specific types of posts are more engaging for the community. Facebook and Twitter interactions vary depending upon the type of posts, demonstrating that citizens are using Facebook and Twitter to interact in different ways.

Research limitations/implications

The findings presented here give police agencies’ insight on how to appropriately adjust their use of social media to fulfill the needs of the citizens and optimize interactions with the community.

Originality/value

This is the first study to systematically examine and analyze the varieties in the use of social media by traditional American local police departments and their interactions with citizens.

Details

Online Information Review, vol. 41 no. 6
Type: Research Article
ISSN: 1468-4527

Keywords

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Article
Publication date: 10 June 2019

Wu He, Xin Tian and Feng-Kwei Wang

Few academic studies specifically investigate how businesses can use social media to innovate customer loyalty programs. The purpose of this paper is to present an…

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1828

Abstract

Purpose

Few academic studies specifically investigate how businesses can use social media to innovate customer loyalty programs. The purpose of this paper is to present an in-depth case study of the Shop Your Way (SYW) program, which is regarded as one of the most successful customer loyalty programs with social media.

Design/methodology/approach

This paper uses case study research as the methodology to uncover innovative features associated with the SYW customer loyalty program. The authors collected the data from SYW’s social media forums and tweets. The data set was analyzed using social media analytics tools including the R package and Lexicon.

Findings

Based on the research results, the authors summarize innovative social media features identified from SYW. The authors also provide insights and recommendations for businesses that are seeking to innovate their customer loyalty programs using social media technologies.

Originality/value

The results of this case study set a good example for businesses which want to innovate and improve their customer loyalty programs using social media technologies. This is the first in-depth case study on the SYW program, one of the most successful customer loyalty programs with social media. The results shed light on how social media can innovate customer loyalty programs in both theory and practice.

Details

Journal of Enterprise Information Management, vol. 32 no. 5
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 13 November 2017

Wu He, Xin Tian, Ran Tao, Weidong Zhang, Gongjun Yan and Vasudeva Akula

Online customer reviews could shed light into their experience, opinions, feelings, and concerns. To gain valuable knowledge about customers, it becomes increasingly…

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3104

Abstract

Purpose

Online customer reviews could shed light into their experience, opinions, feelings, and concerns. To gain valuable knowledge about customers, it becomes increasingly important for businesses to collect, monitor, analyze, summarize, and visualize online customer reviews posted on social media platforms such as online forums. However, analyzing social media data is challenging due to the vast increase of social media data. The purpose of this paper is to present an approach of using natural language preprocessing, text mining and sentiment analysis techniques to analyze online customer reviews related to various hotels through a case study.

Design/methodology/approach

This paper presents a tested approach of using natural language preprocessing, text mining, and sentiment analysis techniques to analyze online textual content. The value of the proposed approach was demonstrated through a case study using online hotel reviews.

Findings

The study found that the overall review star rating correlates pretty well with the sentiment scores for both the title and the full content of the online customer review. The case study also revealed that both extremely satisfied and extremely dissatisfied hotel customers share a common interest in the five categories: food, location, rooms, service, and staff.

Originality/value

This study analyzed the online reviews from English-speaking hotel customers in China to understand their preferred hotel attributes, main concerns or demands. This study also provides a feasible approach and a case study as an example to help enterprises more effectively apply social media analytics in practice.

Details

Online Information Review, vol. 41 no. 7
Type: Research Article
ISSN: 1468-4527

Keywords

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Article
Publication date: 8 February 2021

Xin Tian, Jing Selena He and Meng Han

This paper aims to explore the latest study of the emerging data-driven approach in the area of FinTech. This paper attempts to provide comprehensive comparisons…

Abstract

Purpose

This paper aims to explore the latest study of the emerging data-driven approach in the area of FinTech. This paper attempts to provide comprehensive comparisons, including the advantages and disadvantages of different data-driven algorithms applied to FinTech. This paper also attempts to point out the future directions of data-driven approaches in the FinTech domain.

Design/methodology/approach

This paper explores and summarizes the latest data-driven approaches and algorithms applied in FinTech to the following categories: risk management, data privacy protection, portfolio management, and sentiment analysis.

Findings

This paper details out comparison between different existed works in FinTech with traditional data analytics techniques and the latest development. The framework for the analysis process is developed, and insights regarding the implementation, regulation and workforce development are provided in this area.

Originality/value

To the best of the authors’ knowledge, this paper is first to consider broad aspects of data-driven approaches in the application of FinTech industry to explore the potential, challenges and limitations of this area. This study provides a valuable reference for both the current and future participants.

Details

Information Discovery and Delivery, vol. 49 no. 2
Type: Research Article
ISSN: 2398-6247

Keywords

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Article
Publication date: 20 December 2019

Wu He, Ivan Ash, Mohd Anwar, Ling Li, Xiaohong Yuan, Li Xu and Xin Tian

An organization’s ability to successfully manage intellectual capital is determined by the actions of its employees to prevent or minimize information security incidents…

Abstract

Purpose

An organization’s ability to successfully manage intellectual capital is determined by the actions of its employees to prevent or minimize information security incidents. To prevent more data breaches to intellectual capital, organizations must provide regular cybersecurity awareness training for all personnel. The purpose of this paper is to investigate the effect of different evidence-based cybersecurity training methods on employees’ cybersecurity risk perception and self-reported behavior.

Design/methodology/approach

The study participants were randomly assigned into four groups (i.e. malware report, malware videos, both malware report and malware videos and no interventions) to assess the effects of cybersecurity training on their perceptions of vulnerability, severity, self-efficacy, security intention as well as their self-reported cybersecurity behaviors.

Findings

The results show that evidence-based malware report is a relatively better training method in affecting employees’ intentions of engaging in recommended cybersecurity behaviors comparing with the other training methods used in this study. A closer analysis suggests whether the training method contains self-relevant information could make a difference to the training effects.

Originality/value

This paper reports an in-depth investigation on how different evidence-based cybersecurity training methods impact employees’ perceptions of susceptibility, severity, self-efficacy, security intention as well as on their self-reported cybersecurity behaviors.

Details

Journal of Intellectual Capital, vol. 21 no. 2
Type: Research Article
ISSN: 1469-1930

Keywords

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Article
Publication date: 13 November 2019

Xin Tian, Wu He, Chuanyi Tang, Ling Li, Hangjun Xu and David Selover

Research on how to use social media data to measure and evaluate service quality is still limited. To fill the research gap in the literature, the purpose of this paper is…

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1002

Abstract

Purpose

Research on how to use social media data to measure and evaluate service quality is still limited. To fill the research gap in the literature, the purpose of this paper is to open a new avenue for future work to measure the service quality in the service industry by developing a new analytical approach of using social media analytics to evaluate service quality.

Design/methodology/approach

This paper uses social media data to measure the service quality of the airline industry with the SERVQUAL metrics. A novel benchmark data set was created for each SERVQUAL metric. The data set was analyzed through text mining and sentiment analysis.

Findings

By comparing the results from social media with official service quality report from the Department of Transportation, the authors found that the proposed service quality metrics from social media are valid and can be used to estimate the service quality.

Practical implications

This paper presents service quality metrics and a methodology that can be easily adopted by other businesses to assess service quality. This study also provides guidance and suggestions to help businesses understand how to collect and analyze social media data for the purpose of evaluating service quality.

Originality/value

This paper offers a novel methodology that uses text mining and sentiment analysis to help the airline industry assess its service quality.

Details

Journal of Enterprise Information Management, vol. 33 no. 1
Type: Research Article
ISSN: 1741-0398

Keywords

Content available
Article
Publication date: 13 September 2021

Xin Tian, Wu He and Yunfei Xing

Abstract

Details

Information Discovery and Delivery, vol. 49 no. 3
Type: Research Article
ISSN: 2398-6247

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