Examination of fake news from a viral perspective: an interplay of emotions, resonance, and sentiments

Purpose The purpose of this paper is to examine the factors that significantly affect the prediction of fake news from the virality theory perspective. The paper looks at a mix of emotion-driven content, sentimental resonance, topic modeling and linguistic features of news articles to predict the probability of fake news. Design/methodology/approach A data set of over 12,000 articles was chosen to develop a model for fake news detection. Machine learning algorithms and natural language processing techniques were used to handle big data with efficiency. Lexicon-based emotion analysis provided eight kinds of emotions used in the article text. The cluster of topics was extracted using topic modeling (five topics), while sentiment analysis provided the resonance between the title and the text. Linguistic features were added to the coding outcomes to develop a logistic regression predictive model for testing the significant variables. Other machine learning algorithms were also executed and compared. Findings The results revealed that positive emotions in a text lower the probability of news being fake. It was also found that sensational content like illegal activities and crime-related content were associated with fake news. The news title and the text exhibiting similar sentiments were found to be having lower chances of being fake. News titles with more words and content with fewer words were found to impact fake news detection significantly. Practical implications Several systems and social media platforms today are trying to implement fake news detection methods to filter the content. This research provides exciting parameters from a viral theory perspective that could help develop automated fake news detectors. Originality/value While several studies have explored fake news detection, this study uses a new perspective on viral theory. It also introduces new parameters like sentimental resonance that could help predict fake news. This study deals with an extensive data set and uses advanced natural language processing to automate the coding techniques in developing the prediction model.

The co-evolution of remote work and expectations in a COVID-19 world utilizing an expectation disconfirmation theory lens

Purpose As researchers are being called to examine the evolving technology research issues for COVID-19 and other pandemics, remote work has been accelerated and represents the future of work. Although it is known that one of the top forces shaping the future of work is changing employee expectations, the knowledge of remote work during a pandemic remains scant. Thus, this paper aims to determine the impact of remote worker’s expectations on their level of satisfaction and intention to continue to work remotely. Design/methodology/approach Using one of the prominent theories on expectations, Expectation Disconfirmation Theory (EDT), the authors conduct an online survey of 146 individuals who are currently working remotely. Findings By applying EDT, the findings demonstrate that an individual’s expectations regarding remote work impact their level of satisfaction with remote work and intention to continue to work remotely. Incorporating extant research, the findings extend the research stream to indicate that employees’ expectations about remote work significantly impact both their level of satisfaction and level of productivity. Originality/value The discussion elucidates the significance of understanding employee expectations regarding remote work in the evolving new normal. The findings from the study demonstrate the importance of an individual’s expectations regarding remote work on their level of satisfaction with remote work and intention to continue to work remotely. Thus, this study fills a gap in the literature by applying EDT to the remote work context.

Moderated mediation and J-curve emergence in path models: an information systems research perspective

Purpose J-curve relationship analyses can provide valuable insights to information systems (IS) researchers. This paper aims to discuss moderated mediation in IS research and the related emergence of J-curve relationships. Design/methodology/approach Building on an illustrative study in the field of IS, the author Lays out three steps to combine moderation and J-curve analyses, with the goal of more fully understanding the underlying moderated mediation relationships. The paper proposes a new segmentation delta method to test for J-curve emergence, as part of this framework. Findings The paper shows, in the context of this study, the complementarity of moderation and J-curve analyses. Research limitations/implications Currently, IS researchers rarely conduct moderation and J-curve analyses in a complementary way, even though there are software tools, and related methods, which allow them to do so in a relatively straightforward way. Originality/value The analyses were conducted with the software WarpPLS, a widely used tool that allows for moderated mediation and J-curve analyses, in a way that is fully compatible with the set of steps presented in this paper.

Relationship between psychological suzhi and internet addiction among chinese college students

Purpose Despite concerns about the effect of internet addiction, little is known about how psychological suzhi impacts the internet addiction of college students. This paper aims to investigate the relationship between psychological suzhi and internet addiction among college students. Design/methodology/approach Using the college student psychological suzhi scale and internet addiction test, 2,070 college students from 11 universities in North China, East China, South China and Southwest China were tested. Findings The detection rate of internet addiction in this college sample of students was 18.8%. There was a significant negative correlation between students’ psychological suzhi and internet addiction (r = −0.408, p < 0.01). Hierarchical regression analysis showed that adaptability and individuality in psychological suzhi significantly negatively predicted college students’ internet addiction tendency (p < 0.001). Originality/value This study is the first to show a relationship between psychological suzhi and internet addiction in college students. In detail, the adaptability and individuality of college students’ psychological suzhi are protective factors related to internet addiction. The results also suggested that the authors can prevent and intervene in internet addiction by modifying college students’ adaptability and individuality.

How to harnesses digital technologies for pursuing business model innovation: a longitudinal study in creative industries

Purpose This study aims to investigate how manufacturing firms in the creative industries harness digital technologies to undertake business model innovation. Design/methodology/approach This study used in-depth case studies to examine the complex interplay between digital technologies and business model innovation. A longitudinal approach was selected to capture major events both within the firm and in the business environment. Building on the firm’s archival data, interviews and secondary data that was available to the public, the authors carefully analyzed impactful digital technology events and the firm’s responses to the technological changes that occurred over the period of 2004–2020. Findings The findings suggest that digital technologies alone are not sufficient for business model innovation to be successful; support from sociotechnical factors is also required. Additionally, firms should reinvent a new business model when the existing ones seem to start to diminish. Research limitations/implications In this study one firm was examined as the subject, using a qualitative method. This method allowed us to observe complex interplays among the resources required in business models. Future research can combine qualitative methods with computational case studies, which utilize a large volume of quantitative big data. Practical implications The results of this study suggest that managers must ensure that the resources within and outside organizations are loosely connected and are readily available to be mobilized for supporting business model innovation. To enable this, managers must prepare the required resources in advance. Originality/value The current findings add to a growing body of literature on business model innovation and digital technologies. In particular, this study describes the process of how a traditional firm from a least developed country pursues business model innovation with the support of digital technologies.

Implementation of a new childcare Workforce Background Check system

Purpose As child abuse and neglect in childcare settings continue to occur, a quality childcare workforce is imperative. This paper aims to describe how an efficient and effective childcare Workforce Background Check system was developed and implemented to protect both children and childcare staff in the state of Michigan. Design/methodology/approach The user-centered design (UCD) approach was used in the creation and statewide implementation of a new acceptable and usable system, the Michigan childcare background check (CCBC) system. The authors conducted focus groups to obtain user feedback and performed several usability evaluations. This approach was used as guidance for the development process and to evaluate the concept designs for the web application that was created. Findings This paper discusses the overall process of implementing the CCBC program, focusing on successes, barriers and lessons learned in the planning, designing and execution phases. By May 2019, more than 92,069 background checks were conducted on personnel in 8,740 licensed childcare facilities across Michigan. Collaboration across stakeholders in different sectors facilitated the implementation of the new system, while structural barriers and stigma provided barriers to implementation. Practical implications Having individuals with various roles, abilities and technical expertise assist with the development and implementation of the system ensured the usability and acceptability of the new system by all types of users. Social implications The general public expects childcare providers to ensure that their employees meet the highest professional standards. Developing effective, easy-to-use fingerprint-based criminal history background check systems to identify ineligible applicants and monitor current employees is one component of an overall strategy to promote child safety and minimize child abuse and neglect in the childcare environments. Originality/value This paper provides a practical example of how a CCBC system can be developed, implemented and scaled to be used statewide. This approach can be used by other states or other disciplines with a similar context. Plain language summary As child abuse and neglect in childcare settings continue to occur, a quality childcare workforce is imperative. This paper shows how this study uses the UCD approach to create an acceptable and usable system and complete statewide implementation of a new Michigan CCBC program. This resulted in an efficient and effective Workforce Background Check system that is essential to protect both children and childcare staff.

Enhancing decision-making with data quality metadata

Purpose Data quality metadata (DQM) is a set of quality measurements associated with the data. Prior research in data quality has shown that DQM improves decision performance. The same research has also shown that DQM overloads the cognitive capacity of decision-makers. Visualization is a proven technique to reduce cognitive overload in decision-making. This paper aims to describe a prototype decision support system with a visual interface and examine its efficacy in reducing cognitive overload in the context of decision-making with DQM. Design/methodology/approach The authors describe the salient features of the prototype and following the design science paradigm, this paper evaluates its usefulness using an experimental setting. Findings The authors find that the interface not only reduced perceived mental demand but also improved decision performance despite added task complexity due to the presence of DQM. Research limitations/implications A drawback of this study is the sample size. With a sample size of 51, the power of the model to draw conclusions is weakened. Practical implications In today’s decision environments, decision-makers deal with extraordinary volumes of data the quality of which is unknown or not determinable with any certainty. The interface and its evaluation offer insights into the design of decision support systems that reduce the complexity of the data and facilitate the integration of DQM into the decision tasks. Originality/value To the best of my knowledge, this is the only research to build and evaluate a decision-support prototype for structured decision-making with DQM.

Role of interaction quality and trust in use of AI-based voice-assistant systems

PurposeThe rapid growth of artificial intelligence (AI)-based voice-assistant systems (VASs) has created many opportunities for individuals to use VASs for various purposes in their daily lives. However, traditional quality success factors, such as information quality and system quality, may not be sufficient in explaining the adoption and use of AI-based VASs. This study aims to propose interaction quality as an additional, yet more important quality measure that leads to trust in an AI-based VAS and its adoption. Design/methodology/approachThe authors propose a research model that highlights the importance of interaction quality and trust as underlying mechanisms in the adoption of AI-based VASs. Based on survey methodology and data from 221 respondents, the proposed research model is tested with a partial least squares approach. FindingsThe results suggest that interaction quality and trust are critical factors influencing the adoption of AI-based VASs. The findings also indicate that the impacts of traditional quality factors (i.e. information quality and system quality) occur through interaction quality in the context of AI-based VASs. Originality/valueThis research adds interaction quality as a new quality factor to the traditional quality factors in the information systems success model. Further, given the interactive nature of VASs, the authors use social response theory to explain the importance of the trust mechanism when individuals interact with AI-based VASs. Contribution to Impact

Explaining social networking sites’ use continuance from employees’ perspectives

PurposeThis paper aims to better comprehend the psychological elements that drive the adoption of social networking sites (SNS). The paper attempts to explain the reasons why people sustainably use social networking websites in the workplace and how this happens. Design/methodology/approachUsing a survey to collect data that was analyzed using structural equation modeling by applying the partial least squares technique. FindingsThe results indicated that SNS use continuance was due more to habit rather than established perceived and normative beliefs such as satisfaction and social norms. Research limitations/implicationsThe authors recommend that the model in the study be tested in other technology environments to evaluate the external validity of the research study. The research was based on an unspecific platform, but each SNS may have its singularity that should merit further consideration. Practical implicationsPeers or coworker influences were noticeable in shaping one’s normative beliefs to continue using SNS in the organization. In this regard, it will be interesting to identify the mechanisms that raise the awareness of SNS in the employees’ social networks in the organization. Specifically, it will be an advantage to reach out to peers in promoting SNS use in the organization because they speak the same language as their fellow employees. Originality/valueDespite several benefits related to SNS use in organizations, studies showed that most of these technologies are boycotted in the workplace. Although extensive studies are dedicated to understanding information and communication technology use continuance in general, this paper aims to inform both academicians interested in the use of enterprise SNS for business purposes and business actors concerned with growing SNS usage and retaining its users in their organizations. The paper will contribute to information systems continuance literature by integrating and extending two major theoretical frameworks.

Intention to write reviews: influence of personality traits, attitude and motivational factors

Purpose The growth in online shopping activities has made online reviews a useful information source for customers. At the same time, the number of shoppers sharing their experiences through reviews has also increased. Not enough research has been undertaken in the past to examine a comprehensive set of factors that influence review posting behaviour. Further, the influence of personality traits on such behaviour is mostly unexplored. The study aims to examine the impact of the system’s usefulness and ease of use, along with shoppers’ motivation for writing reviews, namely, rewards and associated costs. Design/methodology/approach Using the 3 M model of personality traits, this paper examined the impact of these personality traits on customers’ intent towards writing online reviews. A detailed review of the literature was undertaken to ascertain the pertinent factors, and the corresponding validated scales were obtained. The primary data was collected using an offline survey method, and 275 valid responses were recorded. The hypotheses were investigated through structural equation modelling on analysis of a moment structures 22.0. Findings The study observed the significant effects of both ease of use and usefulness, on shoppers’ attitude. This favourable attitude was further found to have a positive effect on shoppers’ intention to write reviews. Of the eight personality traits as predictors of shoppers’ intention to provide reviews, three (neuroticism, agreeableness and openness) were observed to be significant predictors. It was noted that intrinsic rewards influenced shoppers’ intention. Conversely, extrinsic rewards were found to be insignificant in influencing shoppers’ intention. Costs had a significant negative impact on the intention to write reviews. Practical implications The study presents theoretical and managerial implications. This paper suggests that for writing online reviews, the customers must perceive the review system to be simple, convenient and easy to use. It is pertinent for them to comprehend the usefulness of such reviews. Electronic retailers must highlight how the reviews are read and considered in making buying decisions. They must develop a system that enables the review writers to know the number of shoppers who have purchased the product after reading a particular review. E-retailers must strategize to highlight the intrinsic rewards available for shoppers to motivate them. Originality/value The present study examines the factors that motivate and influence shoppers to write online reviews. Using the conceptual framework of technology acceptance model, the self-determination theory and the 3 M framework of personality traits, the study investigates the factors that motivate shoppers to write reviews. The most significant aspect of the present study is the inclusion of eight personality traits for deciphering the relationship between personality traits and the intention to write reviews.