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Article
Publication date: 14 March 2024

Fangfang Hou, Boying Li, Zhengzhi Guan, Alain Yee Loong Chong and Chee Wei Phang

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social…

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Abstract

Purpose

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Design/methodology/approach

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Findings

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

Originality/value

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

Details

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

Keywords

Article
Publication date: 4 June 2018

Zach W.Y. Lee, Tommy K.H. Chan, M.S. Balaji and Alain Yee-Loong Chong

The purpose of this paper is to examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.

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Abstract

Purpose

The purpose of this paper is to examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.

Design/methodology/approach

A self-reported online survey was conducted among Uber users in Hong Kong. A total of 295 valid responses were collected. The research model was empirically tested using the structural equation modeling technique.

Findings

The results suggested that perceived risks, perceived benefits, trust in the platform, and perceived platform qualities were significant predictors of users’ intention to participate in Uber.

Research limitations/implications

This study bridged the research gaps in the sharing economy literature by examining the effects of perceived risks, perceived benefits, and trust in the platform on users’ intention to participate in the sharing economy. Moreover, this study enriched the extended valence framework by incorporating perceived platform qualities into the research model, responding to the calls for the inclusion of technological variables in information systems research.

Practical implications

The findings provided practitioners with insights into enhancing users’ intention to participate in the sharing economy.

Originality/value

This study presented one of the first attempts to systematically examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.

Details

Internet Research, vol. 28 no. 3
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 9 July 2019

Fangfang Hou, Zhengzhi Guan, Boying Li and Alain Yee Loong Chong

The purpose of this paper is to investigate what factors can affect people’s continuous watching and consumption intentions in live streaming.

12041

Abstract

Purpose

The purpose of this paper is to investigate what factors can affect people’s continuous watching and consumption intentions in live streaming.

Design/methodology/approach

This research conducted a mixed-methods study. The semi-structured interview was deployed to develop a research model and a live streaming typology. A survey was then used for quantitative assessment of the research model. Survey data were analyzed using partial least squares-structural equation modeling.

Findings

The results suggest that sex and humor appeals, social status display and interactivity play considerable roles in the viewer’s behavioral intentions in live streaming and their effects vary across different live streaming types.

Research limitations/implications

This research is conducted in the Chinese context. Future research can test the research model in other cultural contexts. This study can also be extended by incorporating the roles of viewer gender and price sensitivity in the future.

Practical implications

This study provides managerial insights into how live streaming platforms and streamers can improve their popularity and profitability.

Originality/value

The paper introduces a novel form of social media and a new business model. It illustrates what will affect people’s behavioral intentions in such a new context.

Details

Internet Research, vol. 30 no. 1
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 30 September 2022

Boying Li, Fangfang Hou, Zhengzhi Guan and Alain Yee Loong Chong

Charitable crowdfunding features are embedded in social media platforms to encourage pro-social behaviors. Although such new practice allows practitioners to leverage the power of…

1284

Abstract

Purpose

Charitable crowdfunding features are embedded in social media platforms to encourage pro-social behaviors. Although such new practice allows practitioners to leverage the power of a highly connected crowd, accomplishing the fundraising goal is still a challenge. This study seeks to understand what drives the donation intention in charitable crowdfunding features on social media platforms by examining the roles of social experience, empathy and personal impulsiveness.

Design/methodology/approach

A survey questionnaire was distributed to social media users in China to collect data. A total of 206 valid responses were analyzed using structural equation modeling to test the proposed hypotheses.

Findings

The results showed that empathy mediates interaction with the fundraiser and perceived proximity with the donatee on a user's donation intention. We also found that social influence on social media platforms positively influences empathy and donation intention. In addition, personal impulsiveness was found to moderate the relationship between empathy and donation intention.

Originality/value

This study contributes to existing literature and practices. It identifies three dimensions of social experience and examines their effects on donation intention, providing insights into the charitable crowdfunding features on social media. Moreover, this study extends the understanding to empathy by delineating its mediating role in the relationship between social experience and donation intention and examining how personal impulsiveness moderates the effect of empathy on donation intention. Furthermore, this study provides valuable insights for practitioners to craft strategies to stimulate pro-social behaviors and increase donations.

Details

Information Technology & People, vol. 36 no. 6
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 25 February 2022

Meng Chen, Xiaodie Pu, Mengru Zhang, Zhao Cai, Alain Yee-Loong Chong and Kim Hua Tan

Despite the potential influence of data analytics capability on servitization, the understanding of the underlying mechanisms of this influence remains unclear. This study aims to…

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Abstract

Purpose

Despite the potential influence of data analytics capability on servitization, the understanding of the underlying mechanisms of this influence remains unclear. This study aims to explore how data analytics capability affects servitization by examining the mediation effect of bricolage and the conditional role of innovation orientation.

Design/methodology/approach

This study employs the moderated mediation method to examine the proposed research model with archival data and multiple-respondent surveys from 1,206 top managers of 402 manufacturing firms in the Yangtze River Delta area in China.

Findings

Bricolage partially mediates the positive relationship between data analytics capability and servitization, and innovation orientation positively moderates this effect.

Practical implications

Manufacturers can leverage bricolage to materialize data analytics capability for servitization. Manufacturers should also pursue an innovation orientation to fully glean the benefits of bricolage in transforming data analytics capability into servitization.

Originality/value

This study opens the black box of how data analytics capability affects servitization by revealing the underlying mechanism of bricolage and the boundary condition role of innovation orientation for this mechanism. It offers valuable insights for practitioners to leverage data analytics to improve servitization through developing bricolage and cultivating a culture of innovation orientation.

Details

International Journal of Operations & Production Management, vol. 42 no. 4
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 31 December 2020

Hing Kai Chan, Alain Yee Loong Chong and Zhao Cai

Abstract

Details

Industrial Management & Data Systems, vol. 121 no. 1
Type: Research Article
ISSN: 0263-5577

Article
Publication date: 21 November 2023

Yu Han, Anna Yumiao Tian, Woon Kian Chong, Alain Yee Loong Chong and Antony Paulraj

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for…

Abstract

Purpose

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for international sourcing. This data-driven PPM matrix is designed to provide a dynamic and process perspective that can help SMEs survive the disruptions caused by emergency situations such as the global COVID-19 pandemic.

Design/methodology/approach

This research reports on qualitative interviews with experienced informants from 15 SMEs in the manufacturing industry. The authors follow process-based research using a combination of retrospective and real-time case study approaches to gradually unveil the dynamics in segmentation and sourcing strategies in the international sourcing context during the COVID-19 pandemic.

Findings

The findings reveal the dynamics of segmentation and international sourcing strategies during global disruptions and unpack the underlying logic behind the dynamics that is specific to SMEs in emerging economies.

Originality/value

Existing literature on PPM predominantly focuses on static and normal sourcing circumstances. This paper addresses this gap by adopting a dynamic approach to study how sourcing strategies of SMEs from emerging economies evolve in a highly volatile environment from an international sourcing perspective.

Details

International Journal of Operations & Production Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 4 June 2018

Alain Yee Loong Chong, Kok Wei Khong, Teng Ma, Scott McCabe and Yi Wang

The purpose of this paper is to examine what influence travelers’ adoption of online reviews, and whether the online reviews will influence their travel planning decisions.

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Abstract

Purpose

The purpose of this paper is to examine what influence travelers’ adoption of online reviews, and whether the online reviews will influence their travel planning decisions.

Design/methodology/approach

Data were collected from 193 respondents from eWOM websites and analyzed using structural equation modeling.

Findings

The results revealed that eWOM has a significant influence on travel decisions. Furthermore, travelers were willing to adopt information from eWOM and this information was useful in their travel planning and decisions. Gender and time spent on online reviews were found to affect travel planning and decisions. Travelers also found that the reviews and issues raised in eWOM had credibility and were of good quality.

Research limitations/implications

The study was not able to incorporate all factors which may be relevant to this study and so further theoretical development may be necessary to develop the conceptual model. The sample size, while adequate, can be expanded further.

Practical implications

Operators and administrators of eWOM can use these findings to develop more user-friendly interfaces so that more positive reviews and sales can be generated.

Social implications

The results showed that travelers who adopt the information in eWOM will, in turn, use eWOM in their travel planning. This confirms the importance of eWOM and travelers in general will translate their pre-travel decisions into actual travel planning.

Originality/value

This research extended existing eWOM and information system adoption studies and focused on the travel planning context. This research validated the significant roles of eWOM argument quality and credibility in predicting the information usefulness of eWOM.

Article
Publication date: 27 September 2023

Misty Sabol, Joe Hair, Gabriel Cepeda, José L. Roldán and Alain Yee Loong Chong

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and…

Abstract

Purpose

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

Design/methodology/approach

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

Findings

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Research limitations/implications

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

Practical implications

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Originality/value

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.

Details

Industrial Management & Data Systems, vol. 123 no. 12
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 5 September 2018

Mengdi Li, Eugene Ch’ng, Alain Yee Loong Chong and Simon See

Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been…

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Abstract

Purpose

Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been conducted on the multi-class sentiment analysis of tweets. The purpose of this paper is to consider the popularity of emojis on Twitter and investigate the feasibility of an emoji training heuristic for multi-class sentiment classification of tweets. Tweets from the “2016 Orlando nightclub shooting” were used as a source of study. Besides, this study also aims to demonstrate how mapping can contribute to interpreting sentiments.

Design/methodology/approach

The authors presented a methodological framework to collect, pre-process, analyse and map public Twitter postings related to the shooting. The authors designed and implemented an emoji training heuristic, which automatically prepares the training data set, a feature needed in Big Data research. The authors improved upon the previous framework by advancing the pre-processing techniques, enhancing feature engineering and optimising the classification models. The authors constructed the sentiment model with a logistic regression classifier and selected features. Finally, the authors presented how to visualise citizen sentiments on maps dynamically using Mapbox.

Findings

The sentiment model constructed with the automatically annotated training sets using an emoji approach and selected features performs well in classifying tweets into five different sentiment classes, with a macro-averaged F-measure of 0.635, a macro-averaged accuracy of 0.689 and the MAEM of 0.530. Compared to those experimental results in related works, the results are satisfactory, indicating the model is effective and the proposed emoji training heuristic is useful and feasible in multi-class TSA. The maps authors created, provide a much easier-to-understand visual representation of the data, and make it more efficient to monitor citizen sentiments and distributions.

Originality/value

This work appears to be the first to conduct multi-class sentiment classification on Twitter with automatic annotation of training sets using emojis. Little attention has been paid to applying TSA to monitor the public’s attitudes towards terror attacks and country’s gun policies, the authors consider this work to be a pioneering work. Besides, the authors have introduced a new data set of 2016 Orlando Shooting tweets, which will be made available for other researchers to mine the public’s political opinions about gun policies.

Details

Industrial Management & Data Systems, vol. 118 no. 9
Type: Research Article
ISSN: 0263-5577

Keywords

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