Our study proposes and tests a method for developing domain-specific dictionaries tailored for textual analysis in information systems research. Traditionally, dictionaries have been widely used for content classification according to sentiment; however, we introduce an alternative approach focused on creating dictionaries from sentiment-devoid documents. We demonstrate this method by developing a dictionary specific to Securities and Exchange Commission (SEC) investigations. Analyzing 150,432 publicly available SEC documents, we gained insights into the semantics of communications between the SEC and firms. To evaluate the dictionary, we analyzed SEC comment letters to predict the likelihood of firms reporting information technology control weaknesses (ITCWs), information technology audit fees, and cyber risks. Our dictionary outperformed five benchmarking dictionaries, explaining a higher proportion of variance in ITCW likelihood, information technology audit fees, and cyber risks. This study enhances the effectiveness of dictionaries in analyzing sentiment-devoid business and governance documents and results in a specialized dictionary for SEC communications.

Contemporary research has leveraged social network data as a predictive tool for decision-making process in the capital market. Yet, its effectiveness may be compromised by social contagion. This study addresses this problem by introducing conversation-level measures that capture how interactions among investors affect market predictions. Drawing on social contagion theory, we identified three conversation conditions-argument similarity, sentiment similarity, and conversation size-and examined their association with the likelihood of abrupt stock price changes, which indicate a loss of collective wisdom. Our analysis of 18 million StockTwits posts for 859 Initial Public Offerings (2008-2017) reveals that conversations with highly similar arguments, highly similar sentiments, and larger size are significantly associated with an increased likelihood of abrupt stock price changes in the subsequent week. Moreover, out-of-sample tests confirm that monitoring conversational dynamics enhances the predictive power of social network analytics, offering valuable guidance for investors and practitioners. Our study extends the theoretical framework of social contagion by highlighting the importance of the conversation level and provides practical recommendations for refining trading strategies based on social media data.

This paper investigates the association between retail investors’ online activity and the pricing of initial public offerings (IPOs). We utilize data from Google Trends and StockTwits to analyze price revision for 901 U.S. IPOs, and find that the online search count, social media post count, and post sentiment are positively associated with IPO pricing. One-standard-deviation increases in these variables correspond to price revision increases of 9.02%, 50.73%, and 70.22%, respectively. Additionally, online search plays a more significant role in influencing IPO price revision when social media discussions about a specific IPO exhibit higher sentiment inequality among participants.

Synopsis The research problem This paper investigates how corporate social responsibility (CSR) moderates the adverse effect of product failure on promoting tweeting about a firm’s products, which subsequently affects sales growth. Motivation or theoretical reasoning Under the social contract theory, high-CSR-performance firms gain social approval and acceptance as they are perceived to have fulfilled their obligations and met society’s expectations. Society is more forgiving to these firms when they are involved in negative events such as product failure. The test hypotheses We hypothesized that firms’ CSR performance moderates the negative effect of product failure on tweet sentiment and that the increase in tweet sentiment leads to higher future sales growth. Target population We focused on the automotive industry due to its vast consumer base. We sampled all 16 car manufacturers that operate in the US. Adopted methodology Using aspect-based sentiment analysis, we identified 302,718 tweets from Twitter about the quality of cars and extracted the tweet sentiment. We used the car recall records to proxy for product failure. Analyses Multivariate regressions were used to test our hypotheses. Findings We found that firms’ CSR mitigates the negative effect of product failure on tweet sentiment about product quality and, subsequently, promotes sales growth. Our findings show that firms with strong CSR received significantly more net positive tweets than did those with weak CSR. Moreover, a 10% increase in net positive tweets was associated with a 0.43% increase in quarterly sales growth ([Formula: see text]). Of the three CSR types, governance CSR exerted the strongest effect on tweet sentiment and environmental CSR the second, while social CSR ranked the third. This paper extends the literature by investigating the effect of CSR on sales growth by altering social media tweeting.

In this editorial, we introduce the special issue on online fake in human-computer interaction. The special issue comprises five papers, including one literature review paper. We propose a conceptual framework that specifies the processes involved in generating, as well as circumventing, online fake and highlights significant aspects of future HCI- related issues to prevent, detect, and correct online fake. In particular, based on the five papers, we note the importance of HCI research in delegating the prevention, detection, and correction of online fake to artificial intelligence.

Purpose This paper aims to investigate the combined effect of two interventions, perspective taking and incentives, on auditors’ professional skepticism (hereafter skepticism) when auditing complex estimates. Specifically, this paper examines the different ways that perspective taking (management versus inspector) and incentives (absent versus reward versus penalty) combine to impact skepticism. Design/methodology/approach This paper uses an experiment with 177 experienced Big 4 auditors. The experiment used a 2 (management vs inspector perspective) × 3 (absent vs reward vs penalty incentives) between-subjects design. Findings In the absence of incentives, adopting a management perspective raises situational skepticism when measuring skepticism as appropriateness of management’s fair value estimate while adopting an inspector perspective raises situational skepticism when measuring skepticism as need for more evidence. The authors find some evidence that incentives complement perspective-taking by enhancing those aspects of skepticism for which perspective-taking performs poorly. When assessing management assumptions, auditors adopting an inspector perspective enhance their skepticism more substantially than those adopting a management perspective, and this enhancement is greater with rewards than with penalties. However, this study does not detect an interaction between incentive type and perspective-taking on auditor skepticism in relation to gathering additional evidence. Originality/value This paper extends the literature by shifting the focus from a single perspective to a comparison of two perspective-taking approaches and discusses how each of these approaches enhances different aspects of skepticism. This paper also illustrates the importance of the interplay between perspective-taking and incentives in enhancing auditor skepticism.

Extending the literature on information technology control weaknesses (ITCWs), we investigate the strategic role of chief information officers (CIOs) in maintaining adequate internal controls and remediating ITCWs. Drawing on institutional theory and sunk cost effect, we develop three hypotheses. We adopt an archival approach and obtain CIO turnover and ITCW data for 890 distinct firms, finding that: (i) ITCW disclosures may not increase the likelihood of CIO turnover, (ii) CIOs' backgrounds are associated with the likelihood of turnover, and (iii) CIO turnover increases the likelihood of subsequent ITCW remediation. Theoretically, we extend the literature by investigating the strategic role of CIOs in remediating ITCW. Practically, we find that common practices by firms to retain CIOs in ITCW situations are ineffective for ITCW remediation. Firms are encouraged to reconsider these practices.

•Patients form emotional attachments to an MMS, which can induce their active usage of such services.•Patients’ satisfaction with service components influences their overall affective evaluation of using the MMS.•Patients’ reliance on service-component in developing emotional attachments to the service is contingent on decision rationality.

Information quality is critical for a communication portal because there are myriad information types, including textual, audio, video and other complex information types which an organization has to manage. In this study, we examine whether information generated from an in-house developed communication portal of the Hong Kong Government would have higher quality than those sister portals developed by individual government departments using commercial packages. We conducted a survey-based study to understand how users evaluate the information quality of these communication portals. This portal case is interesting because: (1) Hong Kong Government has invested millions of US dollars in its implementation; and (2) the number of potential users is huge (over 53,000).

Social commerce is an extension of e‐commerce, in which social media is leveraged to promote user contributions. Our study asks how interruptions in relation to interface design influence two types of user contributions: creating shared content and appreciating others' content. We use two interface designs, pagination and infinite scrolling, to manipulate the extent of interruptions to social commerce users. On the basis of the capacity theory of attention, we develop five hypotheses. We empirically test our model using a lab experiment and a field study to show that interruptions reduce users' content appreciation but increase their content creation and that user characteristics moderate these effects. The theoretical and practical contributions of our study are discussed.

We examine the factors that encourage employees to whistle-blow wrongdoings in relation to confidentiality breaches. We investigate how their anticipated regret about remaining silent changes over time, how such changes influence their whistle-blowing intentions, and what employee characteristics and organizational policies moderate this relationship. Drawing on attribution theory, we develop three hypotheses. Our experiment findings show that: 1) employees' perceptions of the controllability and intentionality (but not stability) of the wrongdoing act affect how their anticipated regret evolves, 2) anticipated regret increases employees' whistle-blowing intentions, 3) anticipated regret has a stronger effect on whistle-blowing intentions when organizations implement policies that promote efforts to protect information confidentiality, and 4) employees with information technology knowledge have a stronger intention to whistle-blow. Theoretically, our study extends the organization security literature's focus to individuals' whistle-blowing and highlights an IS research agenda around whistle-blowing in relation to confidentiality breaches. Practically, it informs organizations about how to encourage employees to whistle-blow when they observe confidentiality breaches.

For firms in the consumer sector of the economy, tweets about service quality reflect consumer satisfaction, which determines firms’ future earnings. Our study responds to anecdotal evidence indicating that analysts have adopted opinion mining to scrutinize Twitter data in order to detect shifts in consumer behavior and make earnings forecasts. If this anecdotal evidence is accurate, certain tweet characteristics may be associated with the accuracy of earnings forecasts for these firms. Our study draws on the literature on consumer satisfaction and firm earnings to identify possible tweet characteristics and hypothesize their associative relationships with analyst forecast accuracy. We use the airline industry as the study context and extract tweets related to airline service quality from publicly available Twitter data and analyst forecast data from the Institutional Brokers’ Estimate System Academic. We apply content analysis, followed by aspect-based sentiment analysis, to the downloaded tweets. Using regressions, we find that the breadth of coverage and the number of posters are associated positively with forecast accuracy. The valence of tweets differentiates their effects on forecast accuracy: negative tweets enhance forecast accuracy to a greater extent than do positive tweets. We do not detect any association between tweet subjectivity and analyst forecast accuracy. There is a marginal negative association between tweet dispersion and forecast accuracy. We conclude by discussing theoretical and practical contributions.

Our study examines how a company’s engagement in corporate social responsibility (CSR) influences word of mouth (WOM) about the company on Twitter, particularly during a service delay. We use the airline industry as the study context. On the popular social medium Twitter, people post tweets about airline services and raise concerns about service delays when flights are delayed, canceled, or diverted. Drawing on the literature on legitimacy and the halo effect, we argue that a company’s CSR engagement enhances its corporate image, which in turn, influences WOM about the company on Twitter. We predict and find that airlines with better CSR engagement receive more positive word of mouth (PWOM) and less negative word of mouth (NWOM) on Twitter. We also find that service delays reduce PWOM and increase NWOM, with the additional finding that the positive relationship between service delays and NWOM is less strong for airlines with better CSR engagement. We conduct additional analyses to investigate the effects of environmental, social, and governance CSR on PWOM and NWOM. Our study has practical implications in informing companies about the benefits of CSR engagement in relation to public opinion during service delays.

Adding to prior research on internal control material weaknesses (ICMW), our study investigates whether information technology material weaknesses (ITMWs) are associated with CEO/CFO turnover, and whether their turnover will promote subsequent remediation. We find that disclosures of ITMW are positively associated with CEO/CFO turnover; however, only CEO turnover promotes subsequent remediation. Our findings on ITMW are different from the prior findings on ICMW – aligned with prior research on ICMW, ITMWs are associated with CEO/CFO turnover; however, unlike prior research on ICMW suggests, dismissals of CFOs do not promote subsequent remediation of ITMW. Thus, future research should consider ICMW and ITMW separately in the examination of their consequences and remediation.

Financial analysts use tweet analytics to prepare their forecasts, yet little information that describes how they do so exists. To address this gap, we scrutinize the associative relationships between tweets about a company’s service and the dispersion of analyst forecasts about the same company’s financial performance. We developed three sets of hypotheses. We extracted tweets related to airlines from the Twitter data from Archive Team and analyst forecast data from Institutional Brokers’ Estimate System Academic. We obtained airline-related tweets from nearly 200,000 individual Twitter users about 10 airlines during a 55-month study period and ran multiple regressions to test the associations between tweet characteristics and forecast dispersion. Our results suggest that, when more posters generate more tweets about a company’s service, analysts make less dispersed forecasts. In addition, negative (or non-verified) tweets reduce forecast dispersion to a greater extent than positive (or verified) tweets do. Theoretically, this paper confirms that Twitter can be a useful data source to provide analysts with additional information to prepare their forecasts. Practically, our findings provide empirical evidence about how Twitter data is associated with analyst forecast dispersion. We encourage stakeholders (such as analysts from small firms and individual investors) to extract data from Twitter as a supplement to market information when analyzing data.

To prepare for the 2030 "baby-boomer challenge", some governments have begun to implement healthcare reforms over the past two decades. These reforms have led healthcare information systems (HIS) to evolve into a major research area in our discipline. This research area has an increasing individual, organizational, and economic impact. Due to the 2030 "baby-boomer challenge", the number of elderly individuals continues to increase, and they may have chronic illnesses, such as eye problems and Alzheimer's disease. Given the practical need for HIS that support chronic care, we decided to conduct a literature synthesis and identify opportunities for HIS research. Specifically, we present the chronic care model and analyze how IS researchers have discussed HIS to address the needs of patients with chronic illness. Further, we identify research gaps and discuss the research topics on HIS that future work can extend and customize to support these patients. Our results stimulate and guide future research in the HIS area. This paper has the potential to strengthen the body of knowledge on HIS.

By tracking consumers’ browsing and purchase history, web personalization generates taste-matched recommendations for each consumer to stimulate purchases. In addition to taste-matching, mobile personalization matches recommendations to a consumer’s physiological need and current location. These two additional features, referred to as need-matching and location-matching, are believed to be enablers of unplanned purchases. However, mobile advertisers may not be able to generate recommendations that meet all personalization criteria. Hence, mobile recommendations may be imperfect. We examine two questions in relation to imperfect recommendations. First, how do we use a descriptor to promote such recommendations? Second, what personalization criterion should be downplayed to induce unplanned purchases? Drawing upon the theory of mood congruence, we theorize that the effect of imperfect recommendation on consumers’ unplanned purchases depends on their mood. We conducted three field experiments to test our hypotheses. Our findings indicate that (1) consumers in positive moods are more likely to form an urge to buy than those in negative moods, and this difference is larger when the descriptor is partial than when it is complete (Experiment 1); (2) need-matching is more influential on urge to buy for consumers in negative moods than for those in positive moods (Experiment 2); and (3) for taste-and-need-matched recommendations, location-matching exerts a stronger effect on the urge to buy for consumers in negative moods than for those in positive moods (Experiment 3). We validated the relevance of our research findings to practice through interviews with senior executives in personalization solution providers. Pathways for enhancing practical impacts of this line of research are recommended.

Firm participation in open source software (OSS) development is a noteworthy phenomenon and includes two types of firm-participating OSS projects: community founded (developed from an open project) and spinout (spun out from an information technology firm’s internal project). OSS project leaders implement quality controls to improve the quality of developed products. They may not be aware that their implementation of quality controls produces a side effect—quality controls signal unobservable project quality to volunteers and promote volunteers’ continued participation intentions (VCPI). We focus on two quality controls—accreditation and code acceptance, which, respectively, map to the input and output quality of an OSS project—and compare their respective effects on VCPI in community-founded and spinout projects. We propose that accreditation and code acceptance influence VCPI by signaling unobservable input and output quality to volunteers. As we focus on continued participation, we theorize as to how volunteers’ tenure in OSS projects moderates the relationships between the signaling effects of input and output quality controls and VCPI. Furthermore, we theorize as to how the OSS project type moderates the effects of quality controls on VCPI. We surveyed 304 volunteers from 40 OSS projects and constructed a two-level model of project and developer factors to explain VCPI. Our findings indicate that both accreditation and code acceptance enhance VCPI. The signaling effects on VCPI associated with accreditation decline with volunteer tenure, but those associated with code acceptance do not. Accreditation and code acceptance influence VCPI, with community-founded projects exhibiting weaker direct positive effects and spinout projects exhibiting stronger direct positive effects. We discuss the theoretical and practical implications of these findings.