A Theory-Driven Deep Learning Method for Voice Chat–Based Customer Response Prediction

2023 | Information Systems Research | Citations: 0

Authors: Chen, Gang; Xiao, Shuaiyong; Zhang, Chenghong; Zhao, Huimin

Abstract: As artificial intelligence and digitalization technologies are flourishing real- ... Expand

Abstract: As artificial intelligence and digitalization technologies are flourishing real-time, online interaction–based commercial modes, exploiting customers’ purchase intention implied in online interaction processes may foster huge business opportunities. In this study, we target the task of voice chat–based customer response prediction in an emerging online interaction–based commercial mode, the invite-online-and-experience-in-store mode. Prior research shows that satisfaction, which can be revealed by the discrepancy between prior expectation and actual experience, is a key factor to disentangle customers’ purchase intention, whereas black-box deep learning methods empirically promise us advantageous capabilities in dealing with complex voice data, for example, text and audio information incorporated in voice chat. To this end, we propose a theory-driven deep learning method that enables us to (1) learn customers’ personalized product preferences and dynamic satisfaction in the absence of their profile information, (2) model customers’ actual experiences based on multiview voice chat information in an interlaced way, and (3) enhance the customer response prediction performance of a black-box deep learning model with theory-driven dynamic satisfaction. Empirical evaluation results demonstrate the advantageous prediction performance of our proposed method over state-of-the-art deep learning alternatives. Investigation of cumulative satisfaction reveals the collaborative predictive roles of theory-driven dynamic satisfaction and deep representation features for customer response prediction. Explanatory analysis further renders insights into customers’ personalized preferences and dynamic satisfaction for key product attributes. History: Yong Tan, Senior Editor; Jingjing Zhang, Associate Editor. Funding: This work was supported in part by the National Natural Science Foundation of China [Grants 71971067 and 72271059] and the China Postdoctoral Science Foundation [Grant 2022M722394]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1196. Collapse

Topics: customer satisfaction willingness to pay decision making marketing information system customer service

Methods: deep learning experiment machine learning BERT theory development

Social Group Buying as a Marketing Strategy

2023 | HICSS | Citations: 0

Authors: Chen, Huiyan; Peng, Jing; Guan, Mengcheng; Li, Jianbin

Abstract: Social group buying (SGB) is a novel form of group buying that encourages custom ... Expand

Abstract: Social group buying (SGB) is a novel form of group buying that encourages customers to purchase deeply discounted products together with friends. Over the past few years, SGB has become a popular marketing strategy for online sellers to acquire new customers. Using a dataset from an e-commerce platform, we investigate whether and how SGB affects the sales of sellers. We find that enrolling a few products into SGB has a positive spillover effect on the sales of the sellers’ other products, and the effect varies substantially across different types of sellers. Specifically, the positive spillover effect is larger for smaller sellers and more diversified sellers. Moreover, we find that the spillover effect exhibits similar heterogeneity at the brand level, except that it can be negative for large brands and non-diversified brands. This finding suggests that sellers may gain from SGB at the expense of large or non-diversified brands. Collapse

Topics: electronic commerce advertising management marketing management

Methods: difference in differences mathematical model longitudinal research

How smart technology empowers consumers in smart retail stores? The perspective of technology readiness and situational factors

2023 | Electronic Markets | Citations: 0

Authors: Chen, Jiahe; Chang, Yu-Wei

Abstract: Smart retail stores have been gaining momentum in smart retailing. Instead of re ... Expand

Abstract: Smart retail stores have been gaining momentum in smart retailing. Instead of relying on in-store staff like traditional counterparts, smart retail stores provide an unmanned environment purely enabled by various in-store smart technologies that support customers throughout the shopping journey. This unstaffed operating model also enables smart retail stores to provide competitive prices by reducing labor costs. However, studies have overemphasized the unique value offered by smart technology but discounted the common value strengthened in smart retail. This study applies the situational factor framework to identify both unique and common factors empowered by smart technology from a comprehensive perspective; then, technology readiness is incorporated to explore consumer purchase intentions in smart retail stores. A total of 283 survey data were collected and analyzed. The main results indicate that most situational factors have a direct effect on purchase intention, and technology readiness enhances the unique situational factors enabled directly by smart technology. Collapse

Topics: business model innovation management price management accounting

Methods: survey structural equation modeling statistical power analysis partial least squares regression partial least squares path modeling

Token Incentives in a Volatile Crypto Market: The Effects of Token Price Volatility on User Contribution

2023 | Journal of Management Information Systems | Citations: 0

Authors: Chen, Kun; Fan, Yifan; Liao, Shaoyi Stephen

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in bl ... Expand

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in blockchain systems to encourage user participation. Distinct from monetary incentives, token incentives are uncertain in reward magnitude due to the large swings in token prices on crypto markets. By focusing on token price volatility, this study investigates how the reward uncertainty affects user contribution in a tokenized digital platform. Our empirical setting is Steemit, a platform where bloggers write posts and share token rewards based on their posts' popularity. We find that while high token price volatility induces a large volume of blog posts, it diminishes post quality. The dichotomous effects are explained via two mechanisms: users' direct reactions to reward uncertainties and their indirect reactions, mediated by altered token preference amid volatility shocks. Deeply exploring this dynamic process, our results reveal that token price volatility facilitates a platform's network short-term effect but impairs long-term user creativity. Our empirical findings thus extend the literature on blockchain economics and cryptocurrencies and have practical implications for the design of incentive mechanisms on tokenized digital platforms. Collapse

Topics: blog blockchain digital platform cryptocurrency user behavior

Methods: longitudinal research instrumental variables estimation data transformation principal component analysis vector autoregression

Theories: motivation crowding theory

Exploring the value of IoT data as an enabler of the transformation towards servitization: an action design research approach

2023 | European Journal of Information Systems | Citations: 0

Authors: Chen, Kuan-Lin; Lassen, Astrid; Li, Chen; Møller, Charles

Abstract: Servitization is a well-recognised phenomenon in the manufacturing industry. Bus ... Expand

Abstract: Servitization is a well-recognised phenomenon in the manufacturing industry. Business potentials are demonstrated mainly from the marketing perspective on servitization. However, increased digitalisation makes servitization interesting to other research areas. This paper applies the resource-based view (RBV) to argue how to value the data and explore its potential and impact on servitization. We examine the evolving role of information technology (IT), particularly of the Internet of Things (IoT), and the role of data in the servitization journey. This research is based on a longitudinal study of a product-oriented manufacturing company’s transformation towards servitization. The engagement with the company also includes the development of an IT platform that consolidates IoT and enterprise data, which enables managers to explore new data-based insights. Our goal is to investigate the organisation and in particular cross-functional effects of data-based insights and their impact on supporting strategic decision-making. The action design research (ADR) approach is applied to unfold the servitizing activities inside the organisation and extract the lesson learned into the joint domains of servitization and information systems research. First, we argued that exploring the value of data is becoming a more complex process. Rather than having one design perspective, technical concerns, business considerations, and operational purpose must be aligned to frame the value of data to support decision-making. Second, we discuss the emerging managerial implications, especially the role of IT in the transformation. A cross-functional team is a prerequisite to exploring complex transformation projects. Thus, managers must recognise the problematic situation and bootstrap the available organisational resources. Finally, we provide empirical evidence on how scholars and practitioners can address mutual interests by applying the ADR approach to a transformation project. In summary, servitizing a product-centric manufacturing firm to have a digital services business model is a transformation involving complex social and organisational relations. This study advocates resource-based analysis as a lens and demonstrates how IT and data as heterogeneous and imperfectly mobile resources create value for a product-oriented manufacturing company. However, a critical question remains on how to manage the expanding operational condition of a servitizing organisation and its business system to sustain its competitive advantage and win the digital market. Collapse

Topics: mobile system internet of things enterprise information system enterprise resource planning smart device

Methods: action design research experiment qualitative interview longitudinal research design artifact

Theories: resource based view of the firm

Factors Affecting the Use of Blockchain Technology in Humanitarian Supply Chain: A Novel Fuzzy Large-Scale Group-DEMATEL

2023 | Group Decision and Negotiation | Citations: 0

Authors: Chen, Lu; Hendalianpour, Ayad; Feylizadeh, Mohammad Reza; Xu, Haiyan

Abstract: Based on previous evidence, the use of blockchain for improving Supply Chains (S ... Expand

Abstract: Based on previous evidence, the use of blockchain for improving Supply Chains (SCs) regarding humanitarian projects has received attention over the past five years. The present study is innovative in investigating crucial parameters affecting the using of Blockchain Technology (BT) in Humanitarian Supply Chains (HSCs). More precisely, this study emphasizes parameters that affect blockchain in the HSCs and presents a new fuzzy large-scale group decision-making trial and evaluation laboratory (fuzzy large-scale group-DEMATEL) approach to analyze the interdependence of contributing factors for using BT in HSCs. This method consists of two stages: (1) clustering the large-scale group-experts into small subgroups by their characteristics, and (2) identifying the key factors affecting BT in HSCs with a novel fuzzy large-scale group-DEMATEL approach. According to experts, in this study, among the 25 evaluated factors, disintermediation has been identified as the most important one, followed by anonymity and security. A closer look reveals that 13 and 12 factors have been “cause” and “effect” factors, respectively. Our research can be used to promote the effectiveness of using BT in HSCs, so as to promote the proper distribution of relief materials in practical disasters. Collapse

Topics: blockchain database system risk management anonymity decision making

Methods: cluster analysis computational algorithm cross sectional research literature study

Theories: fuzzy set theory

A Sociotechnical Perspective on Predictive Analytics Implementation

2023 | HICSS | Citations: 0

Authors: Chen, Leida; Nath, Ravi; Rocco, Nevina; Lidster, Carolyn

Abstract: Developing an effective business analytics function within a company has become ... Expand

Abstract: Developing an effective business analytics function within a company has become a crucial component to an organization’s competitive advantage today. Predictive analytics enables an organization to make proactive, knowledge-driven decisions. While companies are increasing their investments in data and analytics technologies, little research effort has been devoted to understanding how to best convert analytics assets into positive business performance. This issue can be best studied from the socio-technical perspective in order to gain a holistic understanding of the key factors relevant to implementing predictive analytics. Based upon information from structured interviews with information technology and analytics executives of 11 organizations, this study identifies the socio-technical components that are key to organizations’ implementation of predictive analytics. Collapse

Topics: organization structure computer hardware IS management organizational culture systems development

Methods: machine learning qualitative interview grounded theory

Theories: socio technical theory organizational behavior theory

Introduction to the Minitrack on Crowd-based Platforms

2023 | HICSS | Citations: 0

Authors: Chen, Pei-Yu; Huang, Nina; Gu, Bin

Abstract: ... Expand

Abstract: Collapse

Topics: crowdsourcing crowdfunding platform worker social media online labor market

Methods: difference in differences natural language processing longitudinal research natural experiment machine learning

Theories: signaling theory theory of affordance lemon market theory

How mindfulness decreases cyberloafing at work: a dual-system theory perspective

2023 | European Journal of Information Systems | Citations: 0

Authors: Chen, Qian; Gong, Yeming; Lu, Yaobin; Chau, Patrick Y.K.

Abstract: Cyberloafing is a prevalent phenomenon in organisations that may cause serious p ... Expand

Abstract: Cyberloafing is a prevalent phenomenon in organisations that may cause serious problems. In previous studies, cyberloafing has been studied as planned and intentional behaviour. Interestingly, we have observed that cyberloafing frequently happens when employees use smartphones to assist with work tasks, but they may not necessarily intend to engage in this activity. We distinguish between active and passive cyberloafing and focus on studying the latter. Based on dual-systems theory, we introduce the construct of mindfulness in the exploration of the antecedences and internal mechanism of passive cyberloafing. We conducted a research survey with employees who use smartphones to assist with work tasks and collected 474 valid questionnaires to examine our research model. The results showed that dual systems are associated with cyberloafing by influencing mind-wandering, and mindfulness significantly decreased mind-wandering when using a smartphone. This study analyses cyberloafing from an innovative neuroscience perspective and contributes to the literature by proposing a new classification of cyberloafing behaviour, reveals the internal mechanism of how dual systems impact an individual’s behaviour, and introduces mindfulness as an antecedent factor of dual systems. Collapse

Topics: mindfulness smartphone social network information system use personality

Methods: survey data transformation SEM tool factor analysis exploratory factor analysis

Theories: dual-system theory big five model general systems theory

Understanding active participation of online dating services: A mixed methods study

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Qi; Yun, Guobiao; Lu, Jiandong; Wang, Xiaolei

Abstract: Online dating has transformed the way people meet and start relationships. Howev ... Expand

Abstract: Online dating has transformed the way people meet and start relationships. However, online dating platforms typically have many lurkers without active participation. Using a self-regulation framework, this paper aims to study users’ active participation in online dating through a mixed methods study. We first conducted qualitative and quantitative investigations with a machine learning method to explore user active participation and its antecedents. We then developed a theoretical model and conducted a statistical analysis of the model. The empirical findings showed that service quality and trust significantly affected individual active participation in a dating site through attachments to the daters and services. The findings of the study contribute to the extant literature by analyzing user participation in online dating from an attachment perspective. Collapse

Topics: service quality online dating participatory design online dating service Python

Methods: design methodology mixed method qualitative coding machine learning machine learning method

Theories: attachment theory marketing theory