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.

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.

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.

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.

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.

User-centric design within organizations is crucial for developing information technology that offers optimal usability and user experience. Personas are a central user-centered design technique that puts people before technology and helps decision makers understand the needs and wants of the end-user segments of their products, systems, and services. However, it is not clear how ready organizations are to adopt persona thinking. To address these concerns, we develop and validate the Persona Readiness Scale (PRS), a survey instrument to measure organizational readiness for personas. After a 12-person qualitative pilot study, the PRS was administered to 372 professionals across different industries to examine its reliability and validity, including 125 for exploratory factor analysis and 247 for confirmatory factor analysis. The confirmatory factor analysis indicated a good fit with five dimensions: Culture readiness, Knowledge readiness, Data and systems readiness, Capability readiness, and Goal readiness. Higher persona readiness is positively associated with the respondents' evaluations of successful persona projects. Organizations can apply the resulting 18-item scale to identify areas of improvement before initiating costly persona projects towards the overarching goal of user-centric product development. Located at the cross-section of information systems and human-computer interaction, our research provides a valuable instrument for organizations wanting to leverage personas towards more user-centric and empathetic decision making about users.

As a business innovation in the e-commerce marketplace, the use of live streams to boost sales has become an important strategy for e-tailers on major e-commerce platforms globally. However, little theoretical research has been conducted to understand the role of streamers and products in live streaming commerce. Thus, in this study, to examine consumers' perceived diagnosticity and purchase intention, we adopt a 2 (streamer type) × 2 (product type) × 2 (brand awareness) experimental design and conduct a field experiment at a university in southern China, drawing on stimulus-organism-response (SOR) theory. Our results indicate that when a product is recommended by an influential streamer during an e-commerce live stream or has high brand awareness, consumers perceive a high level of diagnosticity, which improves their purchase intention. However, we find no significant effect of product type on the perceived diagnosticity of viewers watching e-commerce live streams. We also discuss the implications of our findings for both theory and practice.

Distributed agile software development (DASD) has gained much popularity over the past years. It relates to Agile Software Development (ASD) being executed in a distributed environment due to factors such as low development budget, emerging software application markets and the need for more expertise. DASD faces a number of challenges with respect to coordination and communication issues. Task allocation in such an environment thus becomes a challenging task. Adopting proper task allocation strategy is crucial to overcome challenges and issues in DASD. Various studies highlight the challenges being faced by DASD and have proposed solutions in the form of framework or models. Knowledge models in the form of ontologies can help to solve certain issues and challenges by providing a proper representation of data that is shareable among distributed teams. Several ontologies with respect to task allocation exist. However, ontologies incorporating factors and dependencies influencing task allocation process in DASD are limited. An ontology representing the knowledge related to task allocation and coordination is important for proper decision making in organizations. Based on an in-depth literature review and a survey conducted among professionals in industry, this paper proposes an ontology, , that incorporates relevant factors and dependencies to be considered in task allocation and coordination process in DASD environment. The ontology facilitates team coordination through effective communication and task allocation by defining the concepts to share knowledge and information in an appropriate way. has been properly evaluated and validated by professionals in the field.

Teleworking refers to the utilization of information and communication technologies for work done outside the workplace. The Covid-19 crisis led to increased utilisation of social networking tools within enterprises, especially when working remotely. The aim of their use is often to improve situational awareness, coordination, and collaboration amongst employees. Online social transparency, typically done through social networks or enterprise social software, refers to the voluntary sharing of personal and contextual information such as those relating to their own and team status, intentions, motivation, capabilities, goal priorities besides updates on the physical and social context, with other colleagues. An ad-hoc practice of social transparency can introduce risks such as information overload, social loafing and peer pressure. Despite recognising its adverse effects, there is a lack of systematic methods that identify and assess the risks of online social transparency. In this paper, we present a method to identify and evaluate these within enterprises. We present the method's workflow, stakeholders, the novel artefacts and techniques devised to use and the outcomes to produce. We evaluate our proposed method by applying it in a real organisational context and assess applicability, efficiency, and effectiveness in identifying risks and supporting managers in risk assessment. The results showed that the method gives a framework of thinking and analysis and helps recognize and identify risks in a specialized manner.

Agile development is known for efficient software development practices that enable teams to quickly develop software to cope with changing requirements. Although there is evidence that agile practices are helpful in such environments, the literature does not inform us as to whether agile practices can also be beneficial in hyper-agile environments. Such environments are characterized by an extremely fast pace of change with fluid requirements. COVID-19 vaccine distribution is one such problem that governments have had to deal with. To solve this problem, governments need to come up with robust responses by formulating teams that have the capability to provide software solutions enabling information visibility into the vaccine distribution process. Such emergent teams need to quickly understand the distribution process, oftentimes define the process itself because it might be non-existent, and build software systems to solve the problem in a matter of days. Not much is known about how systems can be developed at such a fast pace. We adopt a clinical research methodology and employ agile software development practices to develop such a mission-critical system. In the process of building the system, we learn important lessons that can be used to adapt and extend agile methodologies to be used in hyper-agile development environments. We offer these lessons as important first steps to understanding the best practices needed to develop software systems that have the capability to provide visibility into the unprecedented health challenge of distribution of life-saving COVID-19 vaccine.

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.

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.

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.