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During the Covid-19 pandemic, social distance regulation calls for non-contact services, making self-service technologies gain much more attention. However, customers found they are pushed into more digital shadow work by employing Self-service technologies (SSTs). This research aims to examine how digital shadow work influences user emotions and behaviors during SSTs use. Based on the grounded theory method (GTM), this draft drives 128 codes and 7 categories to develop the theory of digital shadow work. Operations, consisting of pre-use, during use, and after use, along with the cognitions, including the perception of use-value and time efficiency, act as the trigger of digital shadow work. Achievement emotions, embodying happiness and satisfaction from technology use, result from the perception of high use-value and high time efficiency, while loss emotions, encompassing anger and disappointment from the user experience, generate from the perception of low use-value and low time efficiency, and finally, user responses from the digital shadow work - quitting, continuous and alternative behaviors are found as key factors. The interventing roles of a sense of control, system features, and compensation are also addressed. Examining users’ psychological mechanisms academically contributes to developing the theory of digital shadow work whereas it advances the development of SSTs on a practical side.

This study empirically investigates e-market consumers’ responses to monthly platform discount coupons. Specifically, based on an archival data set obtained from a leading e-marketplace in Korea, our hidden Markov model reveals that there are two different types of consumers on the e-market, those who purchase relatively less but seek temporal seller discounts (Class 1) and those who buy relatively more but are less attracted by such discounts (Class 2). Class 1 consumers purchase products when platform coupons are available but are less likely to buy when platform coupons are all redeemed. On the other hand, Class 2 consumers are willing to purchase products even without platform coupons. Our latent groups demonstrate that the effect of platform promotion is not unidirectional but may depend on the consumer state and class. We discuss the theoretical contributions and managerial implications of our findings.

Nonprofit organisations (NPOs) use data analytics and corresponding visualisations to discover and interpret patterns of donations and donor behaviours, predict future funds, and analyse time series to undertake decisions and resolve issues. Further detailed understanding of these activities in the context of NPOs is required for efficient and effective utilisation of data analytics. This article reports a systematic review of available literature on data analytics applications in NPOs to answer three research questions: (1) What are the proposed approaches and frameworks for adopting and applying data analytics in NPOs? (2) What aspects of data analytics are used for NPO activities and missions? (3) What challenges and barriers face NPOs regarding the adoption and application of data analytics for their missions? We answered the three research questions by collecting and examining data and using it to develop a new taxonomy. The results show the utilisation of data analytics applications by NPOs has not been examined in depth, indicating the need for further research. This study contributes to the literature by providing insights on the existing use of data analytics applications in various domains, and their benefits and drawbacks for NPOs. This study also presents future research directions.

Social media has become one of the most popular channels to keep updated with daily news because it can quickly and easily access information. This advantage is used by malicious people to spread fake news widely. Since the COVID-19 pandemic, fake news has become a huge social problem, causing people to panic and misunderstand how to cure or protect themselves from the virus. So, the goal of this research is to use deep learning as the Recurrent Neural Network (RNN) model to find fake news about COVID-19 in the Thai language on social media and help filter information by classifying real and fake news.

This study examines the impact of strategic technological innovations (e.g., adoption of fourth industrial revolution (4IR) technologies) on firms’ productivity. To estimate the heterogeneous effects of innovation efforts on firms’ labor productivity, this paper employs a quantile regression model and calculates higher moments of the empirical distributions. This study uses data from 11,654 Korean firms that responded to surveys in 2017 and 2018, comprising 23,308 observations. Our empirical results find that 4IR technology adoption has a significant impact on labor productivity for firms across all quantiles, while the estimates of 4IR technology adoption coefficient on labor productivity are much larger in upper quantiles. This estimated impact of adopting 4IR technology on labor productivity at the upper quantile differs compared to the estimated impact of another innovation strategy, or internal R&D. Notably, adopting 4IR technology increases the median labor productivity of firms and the kurtosis of its distribution. Thus, firms that adopted 4IR technology show labor productivity gains more consistently than those that did not, with few outliers.

Given the dearth of studies on Healthcare Information Systems in public hospitals, the present study proposes a conceptual framework for measuring Information Technology (IT)-enabled production capability by factoring relative efficiencies of IT and firm-specific resources. We employed cross-sectional data analysis using an output- oriented, variable return-to-scale model, viz., Data Envelopment Analysis (DEA). The study empirically tested the conceptual model based on the secondary data obtained from 31 Tamil Nadu district headquarters public hospitals in India. The results identified only two hospitals that are technically efficient in terms of IT-enabled production capability. The study findings have implications for strengthening health management information systems (HMIS) in public hospitals by deploying optimum IT infrastructure elements. Further, hospital administrators can utilize the study to measure the IT-enabled production capability of a public hospital to undertake benchmarking exercises. The conceptual framework with the DEA model is the earliest attempt to measure IT capability objectively in the health services industry.

Flipped learning has become a leading practice in higher educational institutions to combat pedagogical challenges of instructors. The present research extends the Unified Theory of Acceptance and Use of Technology framework with technology self-efficacy and openness-to-change to examine the determinants of flipped classroom based instructional model adoption by the academicians of higher educational institutions. With the help of 243 sample data, the current study’s structural model was tested using covariance-based structural equation modeling. Study model has shown that performance expectancy, effort expectancy, social influence, technical self-efficacy and openness to change predict the behavioral intention. Further behavioral intention and facilitating conditions predict the Use Behavior. Findings of the study led to derive a number of theoretical and practical implications.

Electronic word of mouth (eWOM), such as consumer ratings, reviews, and comments, is an important information source influencing consumers’ behavior and purchase decisions. Prior studies about the effects of eWOM on movie success focus on box office revenue and DVD sales. As the video-on-demand (VOD) market has been growing rapidly in terms of revenue and number of users, research on movie success that focuses on this context is imperative. In addition, prior research concentrates on a single eWOM source and neglects the importance of the relative impact of different eWOM sources. Using eWOM data and movie ranking data of 111 unique movies over three months period, this research analyzes the relative impact of eWOM from internal vs. external sources and professional vs. general users on movie success in the context of VOD industry. Results suggest that eWOM from external sources has a significant impact on movie success at the VOD platform. Moreover, the general audience’s opinion is more influential on movie success compared with movie critics’ opinions. The findings demonstrate that eWOM from external sources and general users plays a critical role in the information search and behavior of consumers and movie success.

Observational Learning (OL) in Information Systems (IS) literature, inferring product quality from the popularity as an aggregated summary of the purchase history, differs from Word of Mouth (WOM) effects in that OL offers less information and thus leaves more room for interpretation of the quality signal. Our study empirically tests the asymmetric effect of the popularity of a platform on a sale conducted on that platform (within-popularity effect) and the asymmetric spillover effects of the popularity of a platform on sales conducted on the other platform (between-popularity effect) using multihoming games across two representative mobile platforms, i.e., Google Play and Apple’s App Store. Consideration of the multihoming games gives salience to the asymmetries by controlling for matched game quality, a possible cause of simultaneity. We exploit a diverse panel data framework to systematically address unavoidable econometrical issues and a dynamic panel data model to control endogeneity of autoregression. Finally, by applying z-test to compare two matched pairs of coefficients, we found that the within-popularity of the Google Play is significantly greater than that of the App Store, whereas the between-popularity is significantly less. We speculate that contextual information, that is, information publicly available about a platform’s policy, moderates the interpretation of OL signals, causing asymmetric effects.

Museums in modern society serve to a broader public than their early predecessors. In response to such transition, many art museums now open digital exhibitions to provide immersive experience and maximize user interaction. This study aims to find facilitators of mass popularity in the field of art by identifying the effect of specific features of digital exhibitions – animated image and storytelling description – on museum visitors’ immersive experience and willingness-to-pay price premium (WTP). By performing an online-based two (art types: still image vs. animated image) by two (description types: informative description vs. storytelling description) experiment, we find that animated images and storytelling description enhance experiential value and imagery vividness, the two aspects of immersion, and WTP. Furthermore, the impact of digital exhibition on visitors’ immersive experience and WTP is stronger when animated images and storytelling description are adopted together. This paper contributes to both IS literature and museum industry by identifying specific features and mechanism of digital exhibition that could enhance visitors’ immersive art experience. By studying digital exhibition, which is not bound by physicality of artwork and exhibition space, this study also offers an empirical insight that advocate timely adoption of a “contactless” museum experience.

Since the last few decades, information technology outsourcing has been observed as an instrument for technology transfer and rapid economic development, with the potential to change the fate of the nation. However, many emerging countries, including Nepal, continue to struggle to establish a foothold in the international market; they are perplexed about their path toward outsourcing, and they still have ineffective laws and policies in place. A snowball sampling method was used to collect quantitative data inside Kathmandu valley among outsourcing companies, freelancers, consultants, and policymakers. Data were properly tested for reliability using Cronbach’s Alpha, analysed using exploratory followed by confirmatory factor analysis, and results were confirmed using convergent and discriminant validity. Second-level validation was performed by partial least squares. The researcher has validated a multidimensional structural model with interdependencies between 8 unobserved and 33 observed variables using path analysis and proposed an information technology outsourcing success model for emerging markets from the vendor’s perspective. Similarly, a latent variable ‘setup quality’ was identified as a new construct omitted by previous researchers in the study of IS success. The model shall be interpreted as “the system dimensions - setup quality, system quality and service quality influence the characteristics – communication quality, user satisfaction, and usage of the products or services. The positive impact of mediating factors leads to individual and organizational benefits, resulting in the overall success of information technology outsourcing.”

As an emerging competition, eSports is currently receiving a growing amount of attention, but relatively little research has been conducted on the likelihood of offline watching. Using the push-pull theory, we propose and test a research model of fans’ perception-centered offline game-watching of eSports matches. Half of the 399 eSports fans we surveyed were from Korea (n = 200) and the other half were from China (n = 199). The results indicate that the entertainment atmosphere has the greatest impact on the intention to watch a match offline, followed by the intention to consume beforehand. There is no direct relationship between offline escapism and offline match-watching. In addition, the diverse personalities of fans affected the entertainment atmosphere and the intention to consume beforehand. This research has theoretical and practical implications for the growth of the eSports offline viewing and eSports tourism industries.