Information Technology & Management最新文献

The management of electronic word of mouth (eWOM) is critical in e-commerce. In this study, on the basis of the elaboration likelihood model (ELM), we constructed a model of factors influencing eWOM by dividing merchants' attributes into the central and peripheral routes, which correspond to consumers' systematic and heuristic cognitive modes respectively. We then tested the developed model by using a cross-sectional data set. The results of this study indicate that the degree of competition faced by merchants has a significant negative association with eWOM. Moreover, price level and location moderate the relationship between competition and eWOM. The services of reservation and group buying have positive associations with eWOM. This research has three main contributions. First, we explored the effect of competition on eWOM. Second, we validated the feasibility of applying the ELM to the catering industry by dividing merchant attributes into the central and peripheral routes; this approach is consistent with systematic and heuristic cognitive theories. Finally, this research provides practical suggestions for eWOM management in the catering industry.

Online Health Communities (OHCs) are a type of self-organizing platform that provide users with access to social support, information, and knowledge transfer opportunities. The medical expertise of registered physicians in OHCs plays a crucial role in maintaining the quality of online medical services. However, few studies have examined the effectiveness of OHCs in transferring knowledge between physicians and most do not distinguish between the explicit and tacit knowledge transferred between physicians. This study aims to demonstrate the cross-regional transfer characteristics of medical knowledge, especially tacit and explicit knowledge. Based on data collected from 4716 registered physicians on Lilac Garden (DXY.cn), a leading Chinese OHC, Exponential Random Graph Models are used to (1) examine the overall network and two subnets of tacit and explicit knowledge (i.e., clinical skills and medical information), and (2) identify patterns in the knowledge transferred between physicians, based on regional variations. Analysis of the network shows that physicians located in economically developed regions or regions with sufficient workforces are more likely to transfer medical knowledge to those from poorer regions. Analysis of the subnets demonstrate that only Gross Domestic Product (GDP) flows are supported in the clinical skill network since discussions around tacit knowledge are a direct manifestation of physicians' professional abilities. These findings extend current understanding about social value creation in OHCs by examining the medical knowledge flows generated by physicians between regions with different health resources. Moreover, this study demonstrates the cross-regional transfer characteristics of explicit and tacit knowledge to complement the literature on the effectiveness of OHCs to transfer different types of knowledge.

The purpose of this study was to investigate decision-makers' views on changes that robotics will create in welfare services. The purpose was also to discover what the opportunities and challenges are in human-robot interaction during these changes and how to manage these changes. As a research method, an online survey was used. The survey was sent to Finnish decision-makers (N = 184). They were divided into three groups: Techno-positive (n = 66), Techno-neutral (n = 47), and Techno-critical (n = 71). According to the results, more than 80% of the respondents saw that robots can offer support in existing work tasks, and more than 70% saw that the robots can do existing tasks. The most often mentioned challenges were the reduction of interaction and the reduction of human touch. Further, there are various knowledge needs among the respondents. Most of the knowledge needs were not based on the technical use of the robots; rather, they were quite scattered. The results suggest that successful use and implementation of robots in welfare services require a comprehensive plan and change agents. This study suggests that techno-positive people could act as change agents, assisting in implementing the changes. In addition, to manage change in the welfare services it is essential to improve the quality of the information, solve the resistance to change, create organizational awareness, and understanding, and establish a psychological commitment to change the processes.

Shared services have become an important IT-enabled organizational form for providing support business functions to internal users. The information systems that implement and deliver shared services are part of the organizational IT infrastructure that has a twofold effect on firm financial performance. On the one hand, with the shared services model, the IT infrastructure consolidates so that the costs are lowered for providing the common functions firm-wide. On the other hand, the systems delivering the shared services embody the workflow and business functions so that the value of shared services can be gained from improvements in the function performance at the process level. We perceive finance shared services as IT-enabled services for corporate finance and accounting functions, and propose that finance shared services improve firm profitability via cost savings at firm level and via increased working capital efficiency at the process level. We test our hypotheses with data on Chinese public firms from 2008 to 2019. Data analysis results show both direct effect of finance shared services on profitability and mediating effect of working capital efficiency. This study expands our understandings about impacts of shared services, and contributes to empirical research in IT business value.

Although lead scoring is an essential component of lead management, there is a lack of a comprehensive literature review and a classification framework dedicated to it. Lead scoring is an effective and efficient way of measuring the quality of leads. In addition, as a critical Information Technology tool, a proper lead scoring model acts as an alleviator to weaken the conflicts between sales and marketing functions. Yet, little is known regarding lead scoring models and their impact on sales performance. Lead scoring models are commonly categorized into two classes: traditional and predictive. While the former primarily relies on the experience and knowledge of salespeople and marketers, the latter utilizes data mining models and machine learning algorithms to support the scoring process. This study aims to review and analyze the existing literature on lead scoring models and their impact on sales performance. A systematic literature review was conducted to examine lead scoring models. A total of 44 studies have met the criteria and were included for analysis. Fourteen metrics were identified to measure the impact of lead scoring models on sales performance. With the increased use of data mining and machine learning techniques in the fourth industrial revolution, predictive lead scoring models are expected to replace traditional lead scoring models as they positively impact sales performance. Despite the relative cost of implementing and maintaining predictive lead scoring models, it is still beneficial to supersede traditional lead scoring models, given the higher effectiveness and efficiency of predictive lead scoring models. This study reveals that classification is the most popular data mining model, while decision tree and logistic regression are the most applied algorithms among all the predictive lead scoring models. This study contributes by systematizing and recommending which machine learning method (i.e., supervised and/or unsupervised) shall be used to build predictive lead scoring models based on the integrity of different types of data sources. Additionally, this study offers both theoretical and practical research directions in the lead scoring field.

Video live streaming services have reached every corner of the world through the influence of COVID-19. In this study, the business model of a video live streaming platform is examined under a structure in which both a streamer and a platform provider simultaneously have an incentive alignment and a payoff conflict. On the one hand, the streaming platform relies on the efforts of streamers to strengthen its market share; on the other hand, streamers can employ influencer marketing to construct their own additional revenue from commercials, which can affect the sales from the advertisements operated by the platform. In addition, the platform provider can reward talented streamers for their remarkable performance by sharing the subscription revenue with them; however, the adoption of a built-in reward system is perplexing because the platform can levy a commission fee from the money donated to streamers. Combining these practical points, our results indicate that advertorials can still be largely expanded by streamers mastering marketing skills, even if there is high substitution in ad services. In addition, the practice of charging a commission fee from the built-in reward system but sharing the subscription revenue with outstanding streamers can benefit the streaming platform, and their donation loss will be compensated by a higher revenue-sharing ratio.

This paper aims to identify and understand factors affecting insiders' intention to disclose patients' medical information and to investigate how these factors affect the intention to disclose. Based on the literature review on deterrence theory and health information security awareness (HISA), we identify relevant factors and develop a research model explaining insiders' intention to disclose patients' health information. We collect data (N = 105) through scenario-based experiments. Results show that two personal factors, collectivism, and IT proficiency, play a significant role in the model. While collectivism affects two components (health information security regulation awareness and punishment severity awareness) of HISA which influences intention to disclose, IT proficiency moderates the relationship between HISA and intention to disclose. In addition, HISA negatively affects reporting assessment and intention to disclose. This paper aims to fill a research gap in understanding factors affecting insiders' intentions to disclose protected health information. We identify and investigate factors (e.g., collectivism, HISA, reporting assessment, and IT proficiency) that may affect insiders' disclosing intentions. We find that collectivism affects two components of HISA which influence reporting assessment and disclosing intention. We also discover that IT proficiency moderates the relationship between HISA and intention to disclose. Our findings suggest that we need to carefully consider personal factors such as collectivistic nature and IT proficiency in managing insiders' security breaches.

This study highlights information networks for COVID-19 according to race/ethnicity by employing social network analysis for Twitter. First, this study finds that racial/ethnic groups are differently dependent on racial/ethnic key players. Whites and Asians show the highest number of racial/ethnic key players, Hispanics have a racial/ethnic key player, and blacks have no racial/ethnic key player in the top 20. Second, racial/ethnic groups show different characteristics of information resources for COVID-19. Whites have the highest key player group in news media, politicians, and researchers, and blacks show the highest key player group in news media. Asians demonstrate the highest key player group in news media, and Hispanics exhibit institutes as the highest key player group. Lastly, there are some differences in group communications across the race/ethnicity. Whites and blacks show open communication systems, whereas Asians and Hispanics reveal closed communication systems. Therefore, governments should understand the characteristics of communications for COVID-19 according to the race/ethnicity.

Covid 19 presents a great challenge and opportunity for remote working, highlighting the need for electronically-mediated leadership in team tasks and performance. What is the role of leadership in improving utilization of information communication technologies (ICTs) in teamwork? Framed within the e-leadership and project management literature and employing a longitudinal field observation method over 8 months that involves 52 subjects and 172 observations, this study finds that (1) first, strong leaders employ a consistent and high-level use of ICTs throughout the whole process of group work, especially at the planning and closing stages of a project. (2) Second, strong leaders alternate the use of various ICTs to match specific tasks at different phases of the project. Two media platforms-team discussion forum and document sharing- stand out as the most important for strong leaders to build trust and execute tasks. (3) Finally, in a project management setting with a group of transient members with clearly-defined tasks and time-sensitive responsibilities, trust-building is a continual and highly significant leadership responsibility that precedes other leadership responsibilities. Trust is built largely through alternating the use of two rich ICT media (discussion forum and instant messaging) with two lean ICT media (document sharing and presentation display). These findings highlight a significant role of e-leadership in organizations which see the emergence of ICTs especially during crises like Covid 19.

Supplementary information: The online version contains supplementary material available at 10.1007/s10799-021-00354-4.

Despite researchers having averred that big data analytics (BDA) transforms firms' ways of doing business, knowledge about operationalizing these technologies in organizations to achieve strategic objectives is lacking. Moreover, organizations' great appetite for big data and limited empirical proof of whether BDA impacts organizations' transformational capacity poses a need for further empirical investigation. Therefore, this study explores the association between big data analytics management capabilities (BDAMC) and innovation performance via dynamic capabilities (DC), by applying the PLS-SEM technique to analyzing the feedback of 149 firms. Consequently, we ground our arguments on dynamic capability and social capital theory rather than a resource-based view that does not provide suitable explanations for the deployment of resources to adapt to change. Accordingly, we advance this research stream by finding that BDAMC significantly enhances innovation performance through DC. We also extend the literature by disclosing how BDAMC strengthens DC via strategic alignment and social capital.