The Cost of Free: The Effects of “Wait-for-Free” Pricing Schemes on the Monetization of Serialized Digital Content

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Choi, Angela; Rhee, Ki-Eun; Yoon, Chamna; Oh, Wonseok

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, th ... Expand

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, digital entertainment content, which has become increasingly pervasive on online platforms. WFF pricing is a strategy in which consumers are given the option to either wait a certain amount of time to acquire digital content at no cost or pay to consume it immediately. We evaluate the extent to which habit formation and presentbiased preferences driven by the consumption of addictive stock affect individual consumers' willingness to wait (or pay) for content, which, in turn, determines the efficacy of WFF pricing. We also examine the conditions under which consumers switch from waiting for free content to instantaneously purchasing content. Our findings indicate that WFF pricing increases the sales of serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively generates sustained profits in the long run. We found that most consumers who initiate a purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, the results indicate that as a user accumulates free episodes of a specific series, given extended waiting periods, the likelihood of their conversion from a wait-for-free customer to an instant-purchase customer increases. In particular, WFF pricing effectively augments the willingness to pay of low-valuation consumers as habit formation builds up through time with the free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 13%. However, as the number of free episodes consumed goes beyond a threshold, the likelihood of conversion decreases. We conclude with a discussion of managerial implications that can help content providers monetize their serialized digital content products. Collapse

Topics: price management consumer behavior advertising management digital good customer satisfaction

Methods: mathematical model robustness check econometric modeling proportional hazards model survival analysis

Theories: behavioral economics

Designing In-Store Navigation Systems in Physical Retail

2023 | International Conference on Business Informatics | Citations: 0

Authors: Khosrawi-Rad, Bijan; Fischer, Lea Sophie; Kaiser, Carolin; Robra-Bissantz, Susanne

Abstract: Physical retail faces the challenge of remaining attractive to customers in the ... Expand

Abstract: Physical retail faces the challenge of remaining attractive to customers in the age of e-commerce. In-store navigation systems are one way to mitigate this issue. These software systems allow customers to be navigated through the retail store. We derive design requirements (DRs) for in-store navigation systems based on eight interviews with customers and employees of furniture stores. We illustrate the implementation of the DRs in a conceptual prototype designed with the platform "Hololink." Initial evaluation results (n = 20) show that customers perceive such a solution for physical retail as mainly positive. We contribute to research and practice by showing how to design in-store navigation systems. Navigation RequirementCustomer Type 1.1The system should offer navigation through the store. Overlapping 1.2The system should navigate on the shortest way. Collapse

Topics: customer satisfaction user experience mobile application conversational agent usability

Methods: design artifact qualitative interview survey survey design design requirement

Spatial Analytics with Hospitality Big Data: Examining the Impact of Locational Determinants on Customer Satisfaction in the U.S. Hotel Market

2023 | HICSS | Citations: 0

Authors: Lee, Minwoo; Kim, Jinwon; Shin, Hyejo

Abstract: Although hotel location has been recognized as one of the important factors affe ... Expand

Abstract: Although hotel location has been recognized as one of the important factors affecting hotel selection and guest satisfaction, relatively few studies have examined guest satisfaction with hotel location and its locational determinants at a macro level. This study aims to identify the locational determinants of hotel guest satisfaction through big data spatial analytics via a case study of 5,302 hotels in 151 cities in the U.S. Based on the framework of hotel location satisfaction, we classified all location-related factors into three categories: accessibility to points of interest, transport convenience, and surrounding environment. Our findings indicated that hotel property’s proximity to city area, landmark, park, shopping center, and highway as well as, attraction-driven tourism industry specialization, and hotel industry agglomeration were significant determinants. Furthermore, the impacts of these factors were spatially heterogeneous. These findings can provide geographical insights that are critical for developing a customer service experience and satisfaction model. Collapse

Topics: big data geographic information system customer satisfaction online review criminality

Methods: regression analysis method spatial analysis spatial regression case study network analysis

The Role of Sentiment Tendency in Affecting Review Helpfulness for Durable Products: Nonlinearity and Complementarity

2023 | Information Systems Frontiers | Citations: 0

Authors: Li, Jin; Zhang, Yulan; Li, Jianping; Du, Jiangze

Abstract: The online review has become an important pillar in the decision-making process ... Expand

Abstract: The online review has become an important pillar in the decision-making process for purchasing experience products, especially durable goods with relatively high prices. Using a rich data set for automobiles, we quantify the sentiment tendency expressed in textual reviews, and empirically examine the nonlinearly inverted U-shaped relationship between customer satisfaction and sentiment tendency. We then investigate the nonlinear influences of review sentiment and depth on helpfulness. Furthermore, we study the relationship between numerical rating and text contents, i.e., sentiment tendency and review depth, in promoting the review helpfulness, and quantitatively identify the complementary effect of sentiment tendency. Our results indicate that both numerical ratings and sentiments expressed in text contents contribute to an increase in review helpfulness. Compared with polarized reviews, the neutral ones better benefit helpfulness and customer satisfaction. We also find that reviews with moderate depth are more helpful. Based on the empirical findings, we discuss several managerial implications for review system designers and consumers in the durable product market. Collapse

Topics: online review customer satisfaction experience good user-generated content website

Methods: sentiment analysis robustness check natural language processing descriptive statistic language model

Customer Complaint Avoidance: A Randomized Field Experiment of Platform Governance Based on Value Co-Creation and Appropriation

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Zhao, Xia; Song, Peijian; Shi, Lanfei; Xue, Ling; Feng, Fan

Abstract: From the theoretical perspectives of value co-creation and value appropriation ... Expand

Abstract: From the theoretical perspectives of value co-creation and value appropriation in platform governance, this study explores how a platform can design motivation mechanisms to induce the proactive efforts of providers to reduce customer complaints. We conducted a field experiment on a major Chinese peer-topeer real estate platform offering long-term rental properties. Specifically, when a renter (customer) complaint about a host (provider) occurs, we sent reminder messages to other unaffected hosts in the same neighborhoods (as the affected host) and urged them to proactively prevent similar complaints. The reminder messages varied in terms of their emphasis of the roles of different stakeholders in platformbased value co-creation (provider-emphasized vs. customer-emphasized) and how they explicated different value appropriation mechanisms (competition-based vs. cooperation-based). Results show that compared to the control message, customer-emphasized messages effectively motivated providers' proactive efforts to reduce customer complaints. Contrastingly, provider-emphasized messages led to the undesirable outcome of increasing customer complaints, possibly due to providers' shirking behavior. We also found that a competition-based value appropriation mechanism strengthened the motivating effect, whereas a cooperation-based mechanism undermined the motivating effect. The study provides important theoretical and practical implications for platforms on the design of effective governance mechanisms. Collapse

Topics: participatory design platform governance peer-to-peer model digital ecosystem service quality

Methods: design methodology experimental group experiment Student's t-test survey

Theories: agency theory

Artificially Human: Examining the Potential of Text-Generating Technologies in Online Customer Feedback Management

2023 | International Conference on Information Systems | Citations: 0

Authors: Katsiuba, Dzmitry; Kew, Tannon; Dolata, Mateusz; Gurica, Matej; Schwabe, Gerhard

Abstract: Online customer feedback management plays an increasingly important role for bu ... Expand

Abstract: Online customer feedback management plays an increasingly important role for businesses. Yet providing customers with good responses to their reviews can be challenging, especially as the number of reviews grows. This paper explores the potential of using generative AI to formulate responses to customer reviews. Using advanced NLP techniques, we generated responses to reviews in different authoring configurations. To compare the communicative effectiveness of AI-generated and human-written responses, we conducted an online experiment with 502 participants. The results show that a Large Language Model performed remarkably well in this context. By providing concrete evidence of the quality of AI-generated responses, we contribute to the growing body of knowledge in this area. Our findings may have implications for businesses seeking to improve their customer feedback management strategies, and for researchers interested in the intersection of AI and customer feedback. This opens opportunities for practical applications of NLP and for further IS research. Collapse

Topics: generative AI online review Turing test artificial intelligence marketing management

Methods: survey experiment natural language processing survey design Kruskal Wallis test

Predicting aspect-based sentiment using deep learning and information visualization: The impact of COVID-19 on the airline industry

2022 | Information & Management | Citations: 0

Authors: Chang, Yung-Chun; Ku, Chih-Hao; Nguyen, Duy-Duc Le

Abstract: This study investigates customer satisfaction through aspect-level sentiment ana ... Expand

Abstract: This study investigates customer satisfaction through aspect-level sentiment analysis and visual analytics. We collected and examined the flight reviews on TripAdvisor from January 2016 to August 2020 to gauge the impact of COVID-19 on passenger travel sentiment in several aspects. Till now, information systems, management, and tourism research have paid little attention to the use of deep learning and word embedding techniques, such as bidirectional encoder representations from transformers, especially for aspect-level sentiment analysis. This paper aims to identify perceived aspect-based sentiments and predict unrated sentiments for various categories to address this research gap. Ultimately, this study complements existing sentiment analysis methods and extends the use of data-driven and visual analytics approaches to better understand customer satisfaction in the airline industry and within the context of the COVID-19. Our proposed method outperforms baseline comparisons and therefore contributes to the theoretical and managerial literature. Collapse

Topics: pandemic customer satisfaction visual analytics cloud computing data visualization

Methods: BERT deep learning natural language processing exploratory data analysis sentiment analysis

Theories: construal level theory appraisal theory

Collaborative consumption continuance: a mixed-methods analysis of the service quality-loyalty relationship in ride-sharing services

2022 | Electronic Markets | Citations: 0

Authors: Lim, Weng Marc; Gupta, Gaurav; Biswas, Baidyanath; Gupta, Rohit

Abstract: Extant studies in collaborative consumption have theorized service quality as th ... Expand

Abstract: Extant studies in collaborative consumption have theorized service quality as the distinctive perception of customers. Improved service quality can enable customers to positively influence their perception of the service and lead to continued usage in the future. In this context, our study acknowledges that service quality in collaborative consumption deserves further research. We propose that service quality in collaborative consumption can manifest across different touchpoints. We employ the SERVQUAL framework and Expectation Confirmation Theory as theoretical lenses to explore the service quality-loyalty relationship of app-based ride-sharing services. We apply mixed methods in the form of (i) semi-structured interviews, (ii) text mining and topic-modelling of app reviews, and (iii) Partial-least Squares modelling of responses collected from ride-sharing passengers. The main findings from our study are as follows. First, service quality is manifested across three touchpoints: platform, vendor, and co-sharer. Second, customer satisfaction of collaborative consumption is positively influenced by platform reliability, platform responsiveness, vendor competence, vendor empathy, and co-sharer’s empathy. Third, platform assurance has the least impact on customer satisfaction. Fourth, customer satisfaction positively influences the continuance of collaborative consumption in ride-sharing services. Findings from our study contribute to the theory, practice, and future research on collaborative consumption. Collapse

Topics: ride sharing platform service quality customer satisfaction mobile application collaborative consumption

Methods: qualitative interview survey natural language processing partial least squares path modeling topic model

Theories: SERVQUAL expectation confirmation theory stakeholder theory

Good Robot, Bad Robot: Customer Responses to Norm-Compliant and Norm-Violating Service Robots

2022 | International Conference on Information Systems | Citations: 0

Authors: Stock-Homburg, Ruth; Heitlinger, Lea

Abstract: Service robots that interact with customers have penetrated various industries. ... Expand

Abstract: Service robots that interact with customers have penetrated various industries. With a basis in social identity theory, this study examines how customers respond to frontline service robots (FSRs) by investigating norm-compliant versus norm-violating behaviors compared with similar behaviors by human frontline employees (FLEs). In experimental studies, a black sheep effect occurs, such that customers downgrade norm-violating FLE behaviors more than similar behaviors by FSRs. They also upgrade norm-compliant behaviors by human FLEs more than those of FSRs. In service failures, this effect manifests as greater anger and frustration toward the FLE. We establish the underlying mechanism driving the black sheep effect: customers assign FSRs to an outgroup but categorize FLEs to their social ingroup, across different service encounters and independent of interaction frequency. Collapse

Topics: robotic customer satisfaction customer loyalty social presence technology adoption

Methods: experiment longitudinal research survey design statistical power analysis parametric test

Theories: social identity theory

What to do after a data breach? Examining apology and compensation as response strategies for health service providers

2021 | Electronic Markets | Citations: 11

Authors: Masuch, Kristin; Greve, Maike; Trang, Simon

Abstract: Innovative IT-enabled health services promise tremendous benefits for customers ... Expand

Abstract: Innovative IT-enabled health services promise tremendous benefits for customers and service providers alike. Simultaneously, health services by nature process sensitive customer information, and data breaches have become an everyday phenomenon. The challenge that health service providers face is to find effective recovery strategies after data breaches to retain customer trust and loyalty. We theorize and investigate how two widely applied recovery actions (namely apology and compensation) affect customer reactions after a data breach in the specific context of fitness trackers. Drawing on expectation confirmation theory, we argue that the recovery actions derived from practice, apology, and compensation address the assimilation-contrast model’s tolerance range and, thus, always lead to satisfaction with the recovery strategy, which positively influences customers’ behavior. We employ an experimental investigation and collect data from fitness tracker users during a running event. In the end, we found substantial support for our research model. Health service providers should determine specific customer expectations and align their data breach recovery strategies accordingly. Collapse

Topics: data breach fitness tracker word of mouth mobile system customer satisfaction

Methods: survey experiment partial least squares regression theoretical contribution structural equation modeling

Theories: expectation confirmation theory