Social commerce continues to grow as a channel for firms to engage with consumers. However, few studies have attempted to provide a comprehensive understanding of the role of customer engagement in generating business outcomes. We utilize a sequential mixed methods design and develop a model illustrating the mechanism through which social commerce generates business outcomes via customer engagement based on the structure–conduct–outcome (SCO) framework from the consumer perspective. We use a qualitative study to conceptualize and develop a contextualized structure, consumer conduct, and outcomes in the context of social commerce. We collected data from American consumers using three rounds of surveys and used quantitative analysis to validate our research. The results show that social ties and social media commitment increase brand community commitment, which is positively related to both social media brand recommendation and brand community interaction (two important types of customer engagement). Accordingly, consumers’ double adoption of social commerce leads to brand commitment, in turn affecting brand loyalty and word of mouth. Our study provides an enhanced understanding of customer engagement in social commerce by validating the SCO framework and integrating the dual model of environmental perception and double adoption. It delivers practical insights into how social commerce can be used as a strategic tool for gaining business benefits.

Consumers continue to rely on social commerce for shopping purposes; however, one challenge for businesses in effectively implementing social commerce is the lack of consumer trust. Thus, the goal of this study is to investigate the mechanisms through which social commerce companies can successfully build consumer trust and increase business. From the socio-technical perspective, we identify social commerce usability and sociability as the two technological and social functions, respectively, of social commerce. We investigate the impacts of social commerce usability and sociability on consumers’ cognitive and affective (emotional) appraisals, which in turn affect their trust and social commerce use. The empirical results indicate that social commerce usability and sociability are positively related to cognitive and affective appraisal, both of which positively affect customer trust in social commerce. The results also demonstrate the positive impacts of consumer trust on social commerce use. Our study advances the social commerce literature.

Social media has been integrated into traditional e-commerce, creating an innovative technology-based approach to changing business practice and service, yet few researchers have attempted to provide an understanding of how this approach is changing consumer decision-making and purchase behaviours. Combining the expectation-confirmation theory and the expectation-confirmation model and information systems continuance, we propose a model for social commerce, illustrating how social media is utilised in online shopping as a three-fold process (pre-purchase, purchase, and post-purchase stages) from a consumer perspective. The model consists of three phases: social commerce motivation, social commerce adoption, and e-commerce effectiveness. Using two rounds of surveys, we find that (1) autonomous motivation and controlled motivation have positive effects on social commerce information seeking and sharing, and (2) social commerce information seeking formulates consumers’ pre-purchase decisions, thus affecting their actual purchase outcomes, repurchase intentions, and social commerce information-sharing intentions in the post-purchase stage. In addition, our study indicates that consumers may play dual roles in social commerce: as information seekers in the pre-purchase stage and as information providers in the post-purchase stage. Our findings have important implications for literature and practice.

Abstract An enhanced understanding of the innovative use of artificial intelligence (AI) is essential for organizations to improve work design and daily business operations. This study's purpose is to offer insights into how AI can transform organizations' work practices through diving deeply into its innovative use in the context of a primary AI tool, a chatbot, and examining the antecedents of innovative use by conceptualizing employee trust as a multidimensional construct and exploring employees' perceived benefits. In particular, we have conceptualized employee trust in chatbots as a second‐order construct, including three first‐order variables: trust in functionality, trust in reliability, and trust in data protection. We collected data from 202 employees. The results supported our conceptualization of trust in chatbots and showed that three dimensions of first‐order trust beliefs have relatively the same level of importance. Further, both knowledge support and work–life balance enhance trust in chatbots, which in turn leads to innovative use of chatbots. Our study contributes to the existing literature by introducing the new conceptualization of trust in chatbots and examining its antecedents and outcomes. The results can provide important practical insights regarding how to support innovative use of chatbots as the new way we organize work.

As social networking sites (SNSs) have become quite popular, organizations have used SNSs to support their various business processes. A growing trend is that organizations increasingly encourage consumers to contribute knowledge via SNSs. The contributed knowledge can help organizations to improve their products/services and therefore these contributions have great business value. As consumers are outside of the organization and may not maintain a close relationship, it can be quite challenging to encourage consumer engagement with knowledge sharing on SNSs. This study develops a research model to examine how community identification and trust support consumer knowledge sharing on SNSs, as well as their antecedents. The results demonstrate that community identification and trust facilitate consumer knowledge sharing behavior. This study contributes to the literature by highlighting the important role of community identification in the process of knowledge sharing. The results provide practitioners with guidelines for SNSs and to encourage consumer knowledge sharing.

Evidence-based practice in management assigns a high value to research results as a guide to practices that have been rigorously shown to be effective. To emphasize the practical relevance and outcomes for information systems research, statistical research should generally report its effect sizes. Specifying effect sizes not only reveals the utility of our results, but it also enables evidence-based practitioners to easily compare the known effects of different interventions applied in different studies. Effect size reporting has become a standard practice in many fields, however, though information systems researchers have adopted many other elements of statistical rigor, effect sizes are often overlooked. This paper surveys the current use of effect size calculations in information systems research, explains how such effects sizes are calculated, offers recommendations on when each of the different formulae is appropriate, and provides foundational work toward an index of expected effect sizes in information systems research.

Organizations increasingly use virtual teams to support their business processes. With software development as its context, this study aims to examine how software engineers are motivated to work in virtual teams, as well as the subsequent impacts this has on their programming and collaboration skills development. A theoretical model was developed based on self-determination theory. Data were collected from longitudinal surveys taken by software engineers in China. Our research results show that trust is positively related to software engineers’ autonomous motivation, whereas social influence is positively related to their controlled motivation. Besides, autonomous motivation enhances the amount of effort software engineers put into programming, whereas controlled motivation does not. Programming effort, in turn, increases their programming and collaboration skills. These research findings can advance our understanding about software engineers’ motivations in the context of software development. Our work also has important implications for organizations and software engineers.

Sharing economy services such as bicycle-sharing have become quite popular. In these services, companies maintain systems which allow consumers to conduct sharing activities. Based upon expectation-confirmation theory, we develop a model investigating the antecedents of consumer confirmation and its consequences in the sharing economy context. Specially, we identify two antecedents including perceived performance and perceived risk. Using an empirical study, our results show that perceived performance has a positive impact on confirmation while perceived risk has a negative effect. Confirmation positively affects service satisfaction, which in turn increases continuance intention and recommendation intention. Further, confirmation is negatively related to dissatisfaction, which in turn increases switch intention. Our study clarifies the process of consumers’ decision-making about using sharing economy, and thus making contribution to the sharing economy literature. Practically, it delivers insights for companies into how to retain customers through increasing the value and reducing the risk associated with sharing economy.

The paper draws on customer engagement literature to propose an organic approach to achieving customer loyalty. The organic approach is reflected in customers’ volitional engagement in an online brand community without any deliberate marketing endeavors and incentives from the brand organization. This research employs a longitudinal study focusing on consumers in the United States of America (USA) and examines the relationships between organic customer-engagement behaviors and customer loyalty. Based on expectancy theory, customer perceived benefits are proposed to intervene in these relationships. Results from the longitudinal investigation support the study propositions. Discussion and implications are provided for researchers and practitioners.

Social media is relied upon as a single portal for entertainment, communication, and news. To understand determinants of new sharing, we empirically evaluate data from 188 Facebook users with PLS structural equation modelling. Results support the significant influence of information sharing and status seeking gratifications on news sharing, and that this significance varies across contexts. We find that status seeking gratification has a stronger effect on news sharing when news quality is more emphasized. In other words, sharing low-quality news can be damaging to an individual’s status and they try to avoid it. However, information sharing gratification has a stronger effect on news sharing for those individuals who rely more on credibility and may be employing more heuristic selection approaches. This work has opened up new opportunities for further research and it is hoped that this may contribute to improving the quality and experience of news sharing in social media.

Smart home devices form a significant part of the Internet of Things market and can provide benefits such as convenience and energy efficiency. They also have potential privacy and security risks as they collect information constantly. In order to examine how benefit and risk factors influence individuals’ intentions to adopt smart home devices, we developed a net valence model that integrates both positive factors and risk factors. The model was tested using data collected using an online questionnaire. The results show that individuals tend to ignore the potential risks and focus more on potential benefits resulting from using smart home devices. Performance expectancy and compatibility were found to be positively related to perceived benefits. However, neither effort expectancy nor image were. Among the proposed dimensions of risk, only privacy risk, performance risk, and time risk significantly influenced perceived risk. Security risk and financial risk did not influence it.

Retaining existing users and letting them continue to use the current social networking sites (SNSs) have become increasingly challenging for developers. This study takes a model comparison approach to investigate this important issue. Based on technology acceptance model, self-determination theory, and net-valence model, our study develops four models that explain individuals’ continuance intention. Based on the data collected from U.S. SNS users, all four models can predict individuals’ intention reasonably well, and net-valence model with perceived benefits and risks as second-order constructs explains the largest amount of variance of SNS continuance intention. This study is among the first model comparison studies in the SNS continuance area. It is also among the first to apply self-determination theory and net-valence model to investigate SNS continuance.

The motivation of user-generated content (UGC) is a vital issue for social media providers. This study investigates this issue using the self-determination theory (SDT). The SDT identifies three fundamental human psychological needs, namely the need for competence, autonomy, and relatedness. This study aims to answer the question of how the satisfaction of these needs motivates users to produce UGC and utilizes the multi-study model comparison approach. Two survey studies were conducted in China and the United States. The partial least squares (PLS) analyses confirmed that the SDT indeed explained UGC motivation significantly and that trust beliefs support people’s need for relatedness. Post hoc analyses showed that there were significant differences between Chinese and American culture. Those results make important contributions to theory and practice. For example, practitioners need to motivate users to produce UGC by supporting their psychological needs. Besides, different trust beliefs should be emphasized in different countries.

When the online social networking market is no longer a “blue ocean,” retaining existing users and maintaining their satisfaction with the current social network site (SNS) become SNS providers' most important tasks. This study applies Self-Determination Theory and examines the relationship between trust, relatedness need, and users' satisfaction with SNSs. Using Facebook as the context, we tested our hypotheses with the student sample from a large state university in U.S. The results show that competence and benevolence trust beliefs positively influence relatedness need satisfaction; relatedness need satisfaction and relatedness need level significantly influence uses' satisfaction with SNSs. The theoretical and practical implications of this study are also discussed.

Many firms are considering ‘bring-your-own-device’ (BYOD) programs, under which their employees are allowed to bring their own devices to work and use them for both private and business purposes. This study examines what factors determine an employee's intention to participate in a corporate BYOD program and how such programs affect employer attractiveness. We approach our study of acceptance of corporate BYOD programs from the perspective of technology acceptance research. For this purpose, we propose a modified and extended UTAUT model. The model was tested by surveying students in their final term (n = 444). We show that performance expectancies have the strongest positive effect on intention, while perceived threats negatively impact intention. Finally, behavioural intention was positively associated with employer attractiveness, which leads to clear indications for companies considering establishing corporate BYOD programs. BYOD seems to play an increasingly important role in attracting and retaining future talent.