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Everyday users of professional networks such as LinkedIn are flooded by posts presenting the achievements of their connections (e.g. I got a new job/award). The present research takes a self-discrepancy perspective to examine the mixed-emotional and behavioral consequences of viewing such idealized self-promotional content on professional networks.

The emotional and behavioral consequences following viewership of idealized self-promotional content on LinkedIn are explored through one pilot study (N = 109) and one online experiment (N = 714), which is evaluated using structural equation modeling.

Viewership of idealized self-promotional content on professional social networking sites acts as an emotional double-edged sword for LinkedIn users. Users feel both dejection and symhedonia (i.e. happiness for others), dependent on their reported career-based self-discrepancy. We find the experience of symhedonia to be bound by the relational closeness of the poster (acquaintance vs close friend). Furthermore, we show how resultant emotions drive self-regulatory compensatory IT-use behaviors (i.e. direct resolution, fluid compensation, dissociation, and escapism).

We offer four distinct contributions. Firstly, we disentangle inconsistent findings of mixed emotions by introducing symhedonia to IT literature. Secondly, we investigate the boundary condition of relational closeness. Thirdly, we extend our findings by investigating compensatory-consumption behaviors that stem from mixed-affective outcomes. Finally, we do so in the context of professional networks, which are greatly understudied and are distinctive from personal networks. Practical implications are discussed.

Farmers' risk attitudes and risk perceptions play an essential role in shaping risk management strategies to address risks and uncertainties. Contract farming is considered as one of the feasible approaches to tackle farmers' concerns. However, risk perspectives under various categories have not been included in studies on farmers' preferences for contract farming in the literature, especially in Vietnam. This study aims to determine factors affecting farmers' choices of different contract farming practices.

The explanatory factor analysis (EFA) and multinomial logit model (MNL) were applied to explore the impacts of risk perspectives on farmers' preferences for contract farming. Data have been collected from 211 rice farmers in An Giang Province, “the rice bowl” of the Mekong Delta, Vietnam.

The study found that farm size, cooperatives, extension, market access and trust have significantly impacted on contract participation while a delay payment was a barrier for farmers' motivation to opt for the contract. Farmers' contract choices were also influenced by their risk attitudes and perceptions under different risk dimensions. The financial, policy and human risk-averse behavior predisposed farmers to single out the full contract while the policy and human risk-loving and production, market and finance risk-averse respondents were in favor of the marketing contract. Moreover, the findings indicated that the more farmers concerned about risk of weather and market, the more choices for the full contract, whereas the risk perceptions of weather and policy encouraged farmers to use the limited contract. By contrast, farmers who perceived the impacts of risk of diseases/pests and human were likely to adopt the marketing contract.

This study just focuses on collecting data from farmers’ perspective. Future studies involving stakeholders such as enterprises and policy makers are strongly recommended so as to design suitable contracts and enforce contract schemes effectively in Vietnam.

The findings also contribute to the literature on different types of contracts and the multidimensional aspect of risk for rice production in Vietnam.

This study aims to investigate the impact of FinTech on money laundering within the context of Nigeria. The motivation stems from observations suggesting that FinTech platforms might be used for illicit money transfers, particularly from developed to developing economies. While existing literature predominantly highlights the positive aspects of FinTech, there's a dearth of studies addressing its potential association with money laundering. Current understanding of this relationship relies heavily on anecdotal evidence derived from reported or convicted cases. Thus, the primary goal of this study is to analyze the influence of FinTech on money laundering while also considering the moderating effects of financial regulation and financial literacy as perceived by users. The research delves into regulatory perspectives concerning money laundering and FinTech.

To fulfill the study's objectives, a quantitative research design is used. A survey of 248 FinTech users in Nigeria is conducted using structured questionnaires. Data collected from the questionnaires is analyzed using partial least square structural equation modeling (PLS-SEM).

The quantitative analysis revealed a significant relationship between FinTech and money laundering and that financial regulation moderates the relationship between FinTech and money laundering in Nigeria, but such was not established with respect to financial literacy. The results of the quantitative approach that uses secondary data are consistent with the qualitative approach. FinTech the results indicate the presence of technology induced money laundering in Nigeria. Regulating technology-based anti-money laundering poses serious challenges for developing countries due to the absence of specific laws that mitigate the threats.

The paper focuses on Nigeria as a case study, which may limit the generalizability of the findings to other countries with different FinTech ecosystems, regulatory frameworks and financial literacy levels.

The finding is useful in developing guidelines and regulations by policymakers and strategies by practitioners in relation to FinTech, money laundering, financial regulation and financial literacy. On the basis of the above, the authors recommend regulation at the national and industry level to mitigate the adverse effect of technology on money laundering. Thus, multilateral partnerships can help in tackling tech-induced money laundering through strengthened cooperation.

Money laundering risks: The study highlights that FinTech, while beneficial, also poses significant risks for money laundering activities, especially in developing countries like Nigeria. Regulatory Importance: It emphasizes the critical role of financial regulations in mitigating the risks associated with FinTech and money laundering. Financial Literacy: The paper suggests that financial literacy does not significantly moderate the relationship between FinTech and money laundering, indicating the need for stronger regulatory measures rather than relying solely on financial literacy. Policy Formulation: The findings are crucial for policymakers to formulate strategies that balance the benefits of FinTech with the need to prevent money laundering and ensure financial system integrity.

This research presents a novel approach to methodology, specifically focusing on the qualitative research design, addressing population, sampling techniques and data collection methods. It emphasizes techniques aimed at ensuring measurement quality and achieving research objectives. Data collection used survey questionnaires, while analysis involved both statistical package for social science (SPSS) and PLS-SEM. SPSS facilitated descriptive and preliminary analyses, while PLS-SEM confirmed measurement quality and tested hypotheses. Ethical considerations were paramount throughout the research process, underscoring the commitment to maintaining originality in research endeavors.

In this article, I answer the call to normalize and discuss how ethnographers navigate failure in the field by sharing my own experiences from long-term fieldwork in Malawi. I highlight, particularly, my own struggles with feelings of failure and the role of my interlocutors in helping me navigate and understand these situations.

My argument is based on more than 18 months of ongoing in-depth ethnographic fieldwork in Malawi, where I study the everyday practices of civil servants active in disaster governance, focusing on those working for the Malawi Government Department of Disaster Management Affairs (DODMA).

I use ethnographic vignettes to show how my interlocutors tried to teach me what being a Malawian civil servant is all about, which often came most forcefully to the fore in moments where either I or they deemed that I had failed to behave like one.

This adds new empirical data to the discussions on the various manifestations and roles of failure in ethnographic research, underlining how frictions and feelings of failure are a difficult yet productive and central part of fieldwork and ethnographic data creation.