This page has only limited features, please log in for full access.
New product development to enhance companies’ competitiveness and reputation is one of the leading activities in manufacturing. At present, achieving successful product design has become more difficult, even for companies with extensive capabilities in the market, because of disorganisation in the fuzzy front end (FFE) of the innovation process. Tremendous amounts of information, such as data on customers, manufacturing capability, and market trend, are considered in the FFE phase to avoid common flaws in product design. Because of the high degree of uncertainties in the FFE, multidimensional and high-volume data are added from time to time at the beginning of the formal product development process. To address the above concerns, deploying big data analytics to establish industrial intelligence is an active but still under-researched area. In this paper, an intelligent product design framework is proposed to incorporate fuzzy association rule mining (FARM) and a genetic algorithm (GA) into a recursive association-rule-based fuzzy inference system to bridge the gap between customer attributes and design parameters. Considering the current incidence of epidemics, such as the COVID-19 pandemic, communication of information in the FFE stage may be hindered. Through this study, a recursive learning scheme is established, therefore, to strengthen market performance, design performance, and sustainability on product design. It is found that the industrial big data analytics in the FFE process achieve greater flexibility and self-improvement mechanism on the evolution of product design.
Y.P. Tsang; C.H. Wu; Kuo-Yi Lin; Y.K. Tse; G.T.S. Ho; C.K.M. Lee. Unlocking the power of big data analytics in new product development: An intelligent product design framework in the furniture industry. Journal of Manufacturing Systems 2021, 1 .
AMA StyleY.P. Tsang, C.H. Wu, Kuo-Yi Lin, Y.K. Tse, G.T.S. Ho, C.K.M. Lee. Unlocking the power of big data analytics in new product development: An intelligent product design framework in the furniture industry. Journal of Manufacturing Systems. 2021; ():1.
Chicago/Turabian StyleY.P. Tsang; C.H. Wu; Kuo-Yi Lin; Y.K. Tse; G.T.S. Ho; C.K.M. Lee. 2021. "Unlocking the power of big data analytics in new product development: An intelligent product design framework in the furniture industry." Journal of Manufacturing Systems , no. : 1.
The revolution in the digital economy is forcing the retail pharmacy industry to develop new business models to achieve operational excellence. A large amount of user-generated content on social media can be captured and analysed to help organisations gain insights into market requirements and enhance business intelligence. Accordingly, this study proposes an analytic framework for retail pharmacy organisations to: a) use social media and highlight the most-discussed topics by consumers, b) to identify the key areas for improvement based on the most negative comments received, and c) to determine the connections amongst the important concepts and enhance customer loyalty by adding values to consumers. We conduct an in-depth analysis on the Twitter platforms of the three largest retail pharmacy organisations in the UK: Boots, Lloyds and Superdrug. The findings show that issues with marketing, customer service and product are the key improvement areas for the retail pharmacies. Particularly, Boots received an overall better sentiment performance than Lloyds and Superdrug. We also determine the relationships amongst the important concepts discussed by consumers. The analysis generates insights into the use of social media for supporting pharmacy organisations in developing their social media strategies as well as improving their operations and service quality.
Yuanzhu Zhan; Runyue Han; Mike Tse; Mohd Helmi Ali; Jiayao Hu. A social media analytic framework for improving operations and service management: A study of the retail pharmacy industry. Technological Forecasting and Social Change 2020, 163, 120504 .
AMA StyleYuanzhu Zhan, Runyue Han, Mike Tse, Mohd Helmi Ali, Jiayao Hu. A social media analytic framework for improving operations and service management: A study of the retail pharmacy industry. Technological Forecasting and Social Change. 2020; 163 ():120504.
Chicago/Turabian StyleYuanzhu Zhan; Runyue Han; Mike Tse; Mohd Helmi Ali; Jiayao Hu. 2020. "A social media analytic framework for improving operations and service management: A study of the retail pharmacy industry." Technological Forecasting and Social Change 163, no. : 120504.
The digitalisation in healthcare opens opportunities for more effective chronic disease management. Digitalised medical records are valuable data sources for identifying high-risk patients and facilitating early clinical intervention. However, the liberation of data has plagued adoption amongst physicians as massive data mean more difficult to identify important knowledge from the data. In the cervical cancer context, many patients are adherence to prescription medications only when symptoms appear, beyond the earlier point-in-time of the disease progression. Regular screening is the only way to detect abnormal cells that may develop into cancer if left untreated. Yet, without a comprehensive understanding of the relationship between risk factors and healthcare outcomes, inappropriate screening procedures may be conducted, lengthening the treatment process. Delay in the treatment process may have an irreversible influence on patients’ conditions as chronic diseases progress. This study demonstrates a data-mining framework which extracts knowledge that can advance cervical cancer screening processes in the form of association rules and improves the generalisation potential of the rules for deployment. The knowledge discovered serves as an additional supplement for physicians’ experience and uncovers appropriate screening strategies based on patients’ risk factors, increasing the chances of high-risk patients getting treated for cervical pre-cancers.
Carmen Kar Hang Lee; Ying Kei Tse; G.T.S. Ho; S.H. Chung. Uncovering insights from healthcare archives to improve operations: An association analysis for cervical cancer screening. Technological Forecasting and Social Change 2020, 162, 120375 .
AMA StyleCarmen Kar Hang Lee, Ying Kei Tse, G.T.S. Ho, S.H. Chung. Uncovering insights from healthcare archives to improve operations: An association analysis for cervical cancer screening. Technological Forecasting and Social Change. 2020; 162 ():120375.
Chicago/Turabian StyleCarmen Kar Hang Lee; Ying Kei Tse; G.T.S. Ho; S.H. Chung. 2020. "Uncovering insights from healthcare archives to improve operations: An association analysis for cervical cancer screening." Technological Forecasting and Social Change 162, no. : 120375.
PurposeThis paper provides a practical framework for managers to develop a sustainable supply chain. Given that rapid globalization has increased supply disruption risk, managers have been forced to establish efficient and responsive supply chain strategies. Nevertheless, diverse uncertainty factors, such as risk perception of strategies, have made practical management difficult. Quantifying managers' risk perceptions and applying them to supply chain strategies allows the authors to propose a structural and practical model for managing supply disruption.Design/methodology/approachThe existing structural model is refined by taking subjective factors into account using the analytic hierarchy process. The applicability of the refined model is demonstrated through a comparative case study.FindingsManagers' risk perceptions vary not only among companies but also between managing divisions within a company, which necessitates possible changes in strategy due to environmental turbulence. The principal component analysis (PCA) characterizes managers' risk perceptions that illustrate companies' emphases on disruption risk.Practical implicationsThe proposed approach quantifies risk perception, which enables practitioners to deal with subjective information in quantitative form. Comparative studies clarify differences in perception given different business backgrounds. The results provide managers with in-depth insights for establishing supply chain strategies reflecting their risk perception.Originality/valueQuantification of managers' subjective risk perception clarifies both the trend and the individual features for uncertainties. The results allow the authors to conduct the PCA, which characterizes companies. Comparative studies generalize the results of extant work, shedding light on cross-sectional differences given different business backgrounds. The effectiveness of the approach is confirmed through retrospective interviews with practitioners.
Yuji Sato; Ying Kei Tse; Kim Hua Tan. Managers' risk perception of supply chain uncertainties. Industrial Management & Data Systems 2020, 120, 1 .
AMA StyleYuji Sato, Ying Kei Tse, Kim Hua Tan. Managers' risk perception of supply chain uncertainties. Industrial Management & Data Systems. 2020; 120 (9):1.
Chicago/Turabian StyleYuji Sato; Ying Kei Tse; Kim Hua Tan. 2020. "Managers' risk perception of supply chain uncertainties." Industrial Management & Data Systems 120, no. 9: 1.
This study scrutinises the mechanism between uncertainty factors and supply chain quality risk (SCQR), and to examine the moderating role of supply market thinness (SMT). Drawing on agency theory and resource dependency theory, a conceptual model for the SCQR is proposed. Based on the survey data obtained from 202 managers, we use the structural equation modelling method to test our conceptual model, and the multiple group method to conduct the moderating analysis. We find that the uncertainty factors are associated with managers' perceptions of the probability and magnitude of SCQR. Moderation analysis show that the impacts of technology uncertainty and traceability uncertainty on probability of SCQR, and the impacts of technology uncertainty, testability uncertainty and product complexity on magnitude of SCQR, are moderated by SMT. The validated model provides practitioners with the direction to scrutinise the nature of SCQR, in order to establish effective practical approaches to manage it.
Ying Kei Tse; Minhao Zhang; Wenjuan Zeng; Jie Ma. Perception of supply chain quality risk: Understanding the moderation role of supply market thinness. Journal of Business Research 2020, 122, 822 -834.
AMA StyleYing Kei Tse, Minhao Zhang, Wenjuan Zeng, Jie Ma. Perception of supply chain quality risk: Understanding the moderation role of supply market thinness. Journal of Business Research. 2020; 122 ():822-834.
Chicago/Turabian StyleYing Kei Tse; Minhao Zhang; Wenjuan Zeng; Jie Ma. 2020. "Perception of supply chain quality risk: Understanding the moderation role of supply market thinness." Journal of Business Research 122, no. : 822-834.
This study aims to investigate how Twitter has been used during an international product recall. Based on the SMCC model and the Crisis Response framework, the study proposes a new crisis communication model (SBCC) to analyse the 2016 Mars product recall tweet dataset. The study finds that the platform has mainly been used to ask questions and spread negative information from the news media. It also finds that the information diffusion (retweeting) has positive associations with the number of followers and the use of Hashtags. These findings suggest how organisations should supervise crisis communication and hence can protect reputational assets.
Jie Ma; Ying Kei Tse; Yuji Sato; Minhao Zhang; Zhou Lu. Exploring the social broadcasting crisis communication: insights from the mars recall scandal. Enterprise Information Systems 2020, 15, 420 -443.
AMA StyleJie Ma, Ying Kei Tse, Yuji Sato, Minhao Zhang, Zhou Lu. Exploring the social broadcasting crisis communication: insights from the mars recall scandal. Enterprise Information Systems. 2020; 15 (3):420-443.
Chicago/Turabian StyleJie Ma; Ying Kei Tse; Yuji Sato; Minhao Zhang; Zhou Lu. 2020. "Exploring the social broadcasting crisis communication: insights from the mars recall scandal." Enterprise Information Systems 15, no. 3: 420-443.
As an important part of social innovation, green product innovation (GPI) is widely regarded as a beneficial strategy for firms to achieve sustainable success. While the way to effectively leverage GPI has not been fully invested. To address this lack, this study examines the antecedent role of inter-organizational control mechanism by investigating the nature of the interplay between formal control and social control in relation to green supply chain collaboration. In addition, we probe the impact of GPI on firm triple bottom line due to the inconsistent results in existing literature. Based on a sample of 239 senior managers and directors in the Chinese manufacturing industry, we test the hypotheses through moderated structural equations modelling. The results show that formal control and social control should be applied as complements in promoting GPI, while only working on Moreover, enhance the awareness and adoption of GPI stimulates better environmental performance and social performance as a result. The relationship between GPI and financial performance is mediated by both environmental and social performance. Our findings will help B2B participants understand the GPI and potential sustainable, social and economic outcomes, and support them formulate more effective control mechanism strategies.
Minhao Zhang; Wenjuan Zeng; Ying Kei Tse; Yichuan Wang; Palie Smart. Examining the antecedents and consequences of green product innovation. Industrial Marketing Management 2020, 93, 413 -427.
AMA StyleMinhao Zhang, Wenjuan Zeng, Ying Kei Tse, Yichuan Wang, Palie Smart. Examining the antecedents and consequences of green product innovation. Industrial Marketing Management. 2020; 93 ():413-427.
Chicago/Turabian StyleMinhao Zhang; Wenjuan Zeng; Ying Kei Tse; Yichuan Wang; Palie Smart. 2020. "Examining the antecedents and consequences of green product innovation." Industrial Marketing Management 93, no. : 413-427.
Purpose The purpose of this paper is to investigate attributes that influence Airbnb customer experience by analysing online reviews from users staying in London. It presents a text mining approach to identify a set of broad themes from the textual reviews. It aims to highlight the customers’ changing perception of good quality of accommodations. Design/methodology/approach This paper analyses 169,666 reviews posted by Airbnb users who stayed in London from 2011 to 2015. Hierarchical clustering algorithms are used to group similar words into clusters based on their co-occurrence. Longitudinal analysis and seasonal analysis are conducted for a more coherent understanding of the Airbnb customer behaviour. Findings This paper provides empirical insights about how Airbnb users’ mindset of good quality of accommodations changes over a five-year timespan and in different seasons. While there are common attributes considered important throughout the years, exclusive attributes are discovered in particular years and seasons. Research limitations/implications This paper is confined to Airbnb experiences in London. Researchers are encouraged to apply the proposed methodology to investigate Airbnb experiences in other cities and detect any change in customer perception of quality stay. Practical implications This paper offers implications for the prioritisation of customer concerns to design and improve services offerings and for alignment of services with customer expectations in the sharing economy. Originality/value This paper fulfils an identified need to examine the change in customer expectation across the timespan and seasons in the case of Airbnb. It also contributes by illustrating how big data can be used to uncover key attributes that facilitate the engagement with the sharing economy.
Carmen Kar Hang Lee; Ying Kei Tse; Minhao Zhang; Jie Ma. Analysing online reviews to investigate customer behaviour in the sharing economy. Information Technology & People 2019, 33, 945 -961.
AMA StyleCarmen Kar Hang Lee, Ying Kei Tse, Minhao Zhang, Jie Ma. Analysing online reviews to investigate customer behaviour in the sharing economy. Information Technology & People. 2019; 33 (3):945-961.
Chicago/Turabian StyleCarmen Kar Hang Lee; Ying Kei Tse; Minhao Zhang; Jie Ma. 2019. "Analysing online reviews to investigate customer behaviour in the sharing economy." Information Technology & People 33, no. 3: 945-961.
Airlines have been adopting yield management to optimise the perishable seat control problem and overbooking is a common strategy. This study outlines the connections between yield management, crises, and crisis communication. Using big data captured on a social media platform, this study aims to combine traditional yield management with emerging social big data analytics. As part of this, we use the twitter data on the 2017 United Airline (UA) to analyse the overbooking crisis. Our findings shed light on the importance of a more effective orchestration of yield management to avoid the escalation of crises during crisis communication phases.
Jie Ma; Ying Kei (Mike) Tse; Xiaojun Wang; Minhao Zhang. Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis. Transportation Research Part E: Logistics and Transportation Review 2019, 127, 192 -205.
AMA StyleJie Ma, Ying Kei (Mike) Tse, Xiaojun Wang, Minhao Zhang. Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis. Transportation Research Part E: Logistics and Transportation Review. 2019; 127 ():192-205.
Chicago/Turabian StyleJie Ma; Ying Kei (Mike) Tse; Xiaojun Wang; Minhao Zhang. 2019. "Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis." Transportation Research Part E: Logistics and Transportation Review 127, no. : 192-205.
Product harm scandal can be viewed as a company's nightmare. In many cases, the source of defective or unsafe components may not be the manufacturing firm itself; rather, there may be problems inherent in the supply network. This research aims to investigate the effects of two focused risk management practices, namely supplier development and proactive product recall, on firms' performance. To scrutinise the impact of two types of control mechanisms, we investigate social control and formal control as antecedents of risk management practices, and explore their moderating roles on the relationship between risk management practices and firm performance. Based on the survey-based data obtained from 209 Chinese manufacturers, structural equation modelling and hierarchical regression are used to test the proposed hypotheses. The results show that both supplier development and proactive product recall significantly contribute to financial performance and quality performance. Furthermore, both formal control and social control are the significant antecedents of the two risk management practices. Most importantly, we examine the moderating roles of the control mechanisms on the relationship between the risk management practices and firm performance. Practitioners should be aware that the control mechanisms have different moderating effects, i.e. different type of control mechanism should be employed to facilitate the risk management practices in order to achieve a better firm performance.
Ying Kei Tse; Minhao Zhang; Kim Hua Tan; Kulwant Pawar; Kiran Fernandes. Managing quality risk in supply chain to drive firm's performance: The roles of control mechanisms. Journal of Business Research 2019, 97, 291 -303.
AMA StyleYing Kei Tse, Minhao Zhang, Kim Hua Tan, Kulwant Pawar, Kiran Fernandes. Managing quality risk in supply chain to drive firm's performance: The roles of control mechanisms. Journal of Business Research. 2019; 97 ():291-303.
Chicago/Turabian StyleYing Kei Tse; Minhao Zhang; Kim Hua Tan; Kulwant Pawar; Kiran Fernandes. 2019. "Managing quality risk in supply chain to drive firm's performance: The roles of control mechanisms." Journal of Business Research 97, no. : 291-303.
The primary focus of operations management is to add value through operational processes. Considerable attention has been given to using process improvement (PI) techniques to reduce costs and time, in order to develop a competitive advantage for the wider organization. However, this narrow definition of value at times overlooks the triple bottom line (TBL) which can result in a number of unintended consequences, specifically issues related to environmental and social measures of performance. To address this, a stakeholder theory lens will be used to analyze PI activities within the context of small and medium-sized enterprises. The TBL will be used to complement the stakeholder perspective, to interpret the benefits that are realized from PI activities. This article highlights both the direct benefits from PI as well as more indirect benefits realized by involving a selection of salient stakeholders in PI. It will show how a developed view of PI can provide an important mechanism for delivering improvements to a firm’s TBL. The work concludes by highlighting the contributions made to both PI practice and stakeholder theory, while acknowledging the need for more research on PI, both from a stakeholder perspective and how it impacts a firm’s TBL.
Rupert L. Matthews; Ying Kei (Mike) Tse; Matthew O’Meara Wallis; Peter E. Marzec. A stakeholder perspective on process improvement behaviours: delivering the triple bottom line in SMEs. Production Planning & Control 2019, 30, 437 -447.
AMA StyleRupert L. Matthews, Ying Kei (Mike) Tse, Matthew O’Meara Wallis, Peter E. Marzec. A stakeholder perspective on process improvement behaviours: delivering the triple bottom line in SMEs. Production Planning & Control. 2019; 30 (5-6):437-447.
Chicago/Turabian StyleRupert L. Matthews; Ying Kei (Mike) Tse; Matthew O’Meara Wallis; Peter E. Marzec. 2019. "A stakeholder perspective on process improvement behaviours: delivering the triple bottom line in SMEs." Production Planning & Control 30, no. 5-6: 437-447.
Ying Kei (Mike) Tse; S.H. Chung; Kulwant S. Pawar. Risk perception and decision making in the supply chain: theory and practice. Industrial Management & Data Systems 2018, 118, 1322 -1326.
AMA StyleYing Kei (Mike) Tse, S.H. Chung, Kulwant S. Pawar. Risk perception and decision making in the supply chain: theory and practice. Industrial Management & Data Systems. 2018; 118 (7):1322-1326.
Chicago/Turabian StyleYing Kei (Mike) Tse; S.H. Chung; Kulwant S. Pawar. 2018. "Risk perception and decision making in the supply chain: theory and practice." Industrial Management & Data Systems 118, no. 7: 1322-1326.
Purpose Firms face critical challenges in managing product quality in a global supply chain. In many cases, these challenges could be regarded as an agency problem which is a result of the goal conflict between the supply chain members. To address such agency problem, the purpose of this paper is twofold: first, to explain how risk and reward sharing practices contribute to firms’ quality performance in the supply chain; and second, to identify the drivers of applying risk and reward sharing. Design/methodology/approach The hypothesised model, based on agency theory, is empirically verified by original survey data of 200 Chinese manufacturing companies using the structural equations modelling approach in a context of product recall. Findings Supplier involvement and task programmability are two significant antecedents of risk and reward sharing. Further, the paper shows that risk and reward sharing have a positive effect on quality performance, however, in terms of contribution to quality performance, risk sharing and reward sharing may be substitution practices. Practical implications This research explains how managers could embrace better preparedness for risk and reward sharing in their supply chains. It is also suggested that although risk and reward sharing are seen as efficient means to improve quality performance, such practices should not be treated as a bundle. Originality/value Building on supply partnership literature, this paper contributes to agency theory by providing a solution to the agency problem, i.e., risk and reward sharing and adding to the limited understanding of the antecedents of risk and reward sharing and examining the effects of risk and reward sharing on quality performance.
Ying Kei Tse; Minhao Zhang; Fu Jia. The effects of risk and reward sharing on quality performance. International Journal of Operations & Production Management 2018, 38, 2367 -2388.
AMA StyleYing Kei Tse, Minhao Zhang, Fu Jia. The effects of risk and reward sharing on quality performance. International Journal of Operations & Production Management. 2018; 38 (12):2367-2388.
Chicago/Turabian StyleYing Kei Tse; Minhao Zhang; Fu Jia. 2018. "The effects of risk and reward sharing on quality performance." International Journal of Operations & Production Management 38, no. 12: 2367-2388.
Recently, in China, the issue of poor quality construction has drawn much public attention. This problem is related not only to poor quality control on the part of the construction firm, but also to the use of inadequate materials and inexperienced subcontractors, that is, to poor quality assurance in the construction supply chain. The purpose of this article is to examine supply chain quality management (SCQM) in the construction industry. Using a case-study approach, this research focuses on a Chinese medium-sized private enterprise in order to determine the most efficient way to conduct a high-quality project when collaborating with material suppliers and subcontractors. To this end, we replicate and extend the SCQM practices to help develop a more refined SCQM conceptual model relevant to the construction industry. Based on the different perspectives of managers and engineers, two frameworks are presented to illustrate (1) the correlation between SCQM and purchasing function (PF), and (2) how to work with material suppliers and subcontractors; the proposed models also show how these aspects will influence and control the quality of projects. Although constrained by the limitations inherent in case-study methodology, this article consolidates the work in one particular area of supply chain management. It also succeeds in meeting two core challenges, namely to explicate the interaction between SCQM and PF, and to provide guidance to construction firms on how to deal with SCQM issues with material suppliers and subcontractors.
Wenjuan Zeng; Ying Kei (Mike) Tse; Minmin Tang. Supply chain quality management: An investigation in the Chinese construction industry. International Journal of Engineering Business Management 2018, 10, 1 .
AMA StyleWenjuan Zeng, Ying Kei (Mike) Tse, Minmin Tang. Supply chain quality management: An investigation in the Chinese construction industry. International Journal of Engineering Business Management. 2018; 10 ():1.
Chicago/Turabian StyleWenjuan Zeng; Ying Kei (Mike) Tse; Minmin Tang. 2018. "Supply chain quality management: An investigation in the Chinese construction industry." International Journal of Engineering Business Management 10, no. : 1.
Minhao Zhang; Ying Kei Tse; Bob Doherty; Si Li; Pervaiz Akhtar. Sustainable supply chain management: Confirmation of a higher-order model. Resources, Conservation and Recycling 2018, 128, 206 -221.
AMA StyleMinhao Zhang, Ying Kei Tse, Bob Doherty, Si Li, Pervaiz Akhtar. Sustainable supply chain management: Confirmation of a higher-order model. Resources, Conservation and Recycling. 2018; 128 ():206-221.
Chicago/Turabian StyleMinhao Zhang; Ying Kei Tse; Bob Doherty; Si Li; Pervaiz Akhtar. 2018. "Sustainable supply chain management: Confirmation of a higher-order model." Resources, Conservation and Recycling 128, no. : 206-221.
Social media has recently emerged as a key tool to manage customer relations in industry. This chapter aims to contribute a step-by-step Twitter Analytic framework for analysing the tweets in a fiscal crisis. The proposed framework includes three major sections – demographic analytic, content analytic and integrated method analytic. This chapter provides useful insights to develop this framework through the lens of the recent Volkswagen emission scandal. A sizable dataset of #volkswagescandal tweets (8,274) was extracted as the research sample. Research findings based upon this sample include the following: Consumer sentiments are overall negative toward the scandal; some clustered groups are identified; male users expressed more interest on social media in the topic than female users; the popularity of tweets was closely related with the timing of news coverage, which indicates the traditional media is still playing a critical role in public opinion formation. The limitations and practical contribution of the current study are also discussed.
Ying Kei Tse; Minhao Zhang; Bob Doherty; Paul Chappell; Susan R. Moore; Tom Keefe. Exploring the Hidden Pattern From Tweets. Social Media Marketing 2018, 937 -957.
AMA StyleYing Kei Tse, Minhao Zhang, Bob Doherty, Paul Chappell, Susan R. Moore, Tom Keefe. Exploring the Hidden Pattern From Tweets. Social Media Marketing. 2018; ():937-957.
Chicago/Turabian StyleYing Kei Tse; Minhao Zhang; Bob Doherty; Paul Chappell; Susan R. Moore; Tom Keefe. 2018. "Exploring the Hidden Pattern From Tweets." Social Media Marketing , no. : 937-957.
Yuji Sato; Kim Hua Tan; Ying Kei (Mike) Tse. Investment performance analysis of industrial products: Case of an effluent processing facility at a chemical company. International Journal of Production Economics 2017, 194, 52 -58.
AMA StyleYuji Sato, Kim Hua Tan, Ying Kei (Mike) Tse. Investment performance analysis of industrial products: Case of an effluent processing facility at a chemical company. International Journal of Production Economics. 2017; 194 ():52-58.
Chicago/Turabian StyleYuji Sato; Kim Hua Tan; Ying Kei (Mike) Tse. 2017. "Investment performance analysis of industrial products: Case of an effluent processing facility at a chemical company." International Journal of Production Economics 194, no. : 52-58.
As social media has become an important part of modern daily life, users often share product opinions online and these tend to spike when large companies undergo crises. This paper investigates customer online responses to a large company crisis by uncovering hidden insights in social media comments and presents a framework for handling social media data and crisis management. Analysis of textual Facebook data from users responding to the 2013 horsemeat scandal is presented. In this study, we used a novel comprehensive data analysis framework alongside a text-mining framework to objectively classify and understand customer perceptions during this horsemeat scandal. This framework provides an effective approach for investigating customer perception during a company crisis and measures the effectiveness of crisis management practices which the company has adopted. Our analyses show that social media can provide important insights into customer behaviour during crisis communications.
Ying Kei Tse; Hanlin Loh; Juling Ding; Minhao Zhang. An investigation of social media data during a product recall scandal. Enterprise Information Systems 2017, 12, 733 -751.
AMA StyleYing Kei Tse, Hanlin Loh, Juling Ding, Minhao Zhang. An investigation of social media data during a product recall scandal. Enterprise Information Systems. 2017; 12 (6):733-751.
Chicago/Turabian StyleYing Kei Tse; Hanlin Loh; Juling Ding; Minhao Zhang. 2017. "An investigation of social media data during a product recall scandal." Enterprise Information Systems 12, no. 6: 733-751.
The literature examining the relationship between green supply chain management and firm performance has expanded greatly in recent years. Although researchers maintain that green supply chain management can bring positive financial performance, to date they have ignored the moderating role of the social control mechanism, especially in the context of China. Drawing on social exchange theory, this study aims to contribute to the literature in this field by proposing social control as an effective mechanism to strengthen the impact of green supply chain management on firms’ financial performance. Today, most empirical literature in the field of green supply chain management adopts the static view and overlooks the contextual factors. This study addresses the gap by investigating the green supply chain management in an environment characterized by frequently unavoidable disruptions, and the effectiveness of social control that accommodates this complexity and dynamism. By examining green supply chain management under conditions of environmental dynamism, this study contributes to the literature of interface of green supply chain and resilience. Using a sample of 185 Chinese manufacturers, the theoretical model is empirically verified. The research findings indicate that in a dynamic environment, the joint effect of social control and green supply chain management practices is positive and significant. This paper also discusses the theoretical contribution and managerial implications of the study, outlines the research limitations, and provides recommendations for future research.
Minhao Zhang; Ying Kei Tse; Jing Dai; Hing Kai Chan. Examining Green Supply Chain Management and Financial Performance: Roles of Social Control and Environmental Dynamism. IEEE Transactions on Engineering Management 2017, 66, 20 -34.
AMA StyleMinhao Zhang, Ying Kei Tse, Jing Dai, Hing Kai Chan. Examining Green Supply Chain Management and Financial Performance: Roles of Social Control and Environmental Dynamism. IEEE Transactions on Engineering Management. 2017; 66 (1):20-34.
Chicago/Turabian StyleMinhao Zhang; Ying Kei Tse; Jing Dai; Hing Kai Chan. 2017. "Examining Green Supply Chain Management and Financial Performance: Roles of Social Control and Environmental Dynamism." IEEE Transactions on Engineering Management 66, no. 1: 20-34.
This article outlines a new method for investigating social position through geo-tagged Twitter data, specifically through the application of the geodemographic classification system Mosaic. The method involves the identification of a given tweeter’s likely location of residence from the ‘geo-tag’ attached to their tweet. Using this high-resolution geographic information, each individual tweet is then attributed a geodemographic classification. This article shows that the specific application of geodemographics for discerning between different types of tweeters is problematic in some ways, but that the general process of classifying tweeters according to their position in geographical space is viable and represents a powerful new method for discerning the social position of tweeters. Further research is required in this area, as there is great potential in employing the mobile global positioning system data appended to digital by-product data to explore the intersections between geographical space and social position.
Paul Chappell; Ying Kei (Mike) Tse; Minhao Zhang; Susan Moore. Using GPS Geo-tagged Social Media Data and Geodemographics to Investigate Social Differences: A Twitter Pilot Study. Sociological Research Online 2017, 22, 38 -56.
AMA StylePaul Chappell, Ying Kei (Mike) Tse, Minhao Zhang, Susan Moore. Using GPS Geo-tagged Social Media Data and Geodemographics to Investigate Social Differences: A Twitter Pilot Study. Sociological Research Online. 2017; 22 (3):38-56.
Chicago/Turabian StylePaul Chappell; Ying Kei (Mike) Tse; Minhao Zhang; Susan Moore. 2017. "Using GPS Geo-tagged Social Media Data and Geodemographics to Investigate Social Differences: A Twitter Pilot Study." Sociological Research Online 22, no. 3: 38-56.