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The purpose of this paper is to understand why some US Senators have more low-quality followers than others and the potential impact of low-quality followers on understanding constituent preferences.

For each US Senator, data on Twitter followers was matched with demographic characteristics proven to influence behavior. An OLS regression model evaluated why some Senators attract more low-quality followers than others. Then, observations on the impact of low-quality followers were discussed along with potential effects on information gathering and constituent representation.

This study finds that total followers, ideology and length of time on Twitter are all significant predictors of whether a Senator might attract low-quality followers. Low-quality followers can have wide-ranging implications on Senator’s use of social media data to represent constituents and develop public policy.

The data set only includes Senators from the 115th Congress (2017–2018). As such, future research could expand the data to include additional Senators or members of the House of Representatives.

Information is essential in any decision-making environment, including legislatures. Understanding why some users, particularly public opinion leaders, attract more low-quality social media followers could help decision-makers better understand where information is coming from and how they might choose to evaluates its content.

This study finds two practical implications for public opinion leaders, including Senators. First, accounts must be actively monitored to identify and weed-out low-quality followers. Second, users need to be wary of disinformation and misinformation and they need to develop strategies to identify and eliminate it from the collection of follower preferences.

This study uses a unique data set to understand why some Senators have more low-quality followers than others and the impact on information gathering. Other previous studies have not addressed this issue in the context of governmental decision-making or constituent representation.

This study aims to conceptualize the relationship of perceived artificial intelligence (AI) credibility with consumer-AI experiences. With the widespread deployment of AI in marketing and services, consumer-AI experiences are common and an emerging research area in marketing. Various factors affecting consumer-AI experiences have been studied, but one crucial factor – perceived AI credibility is relatively underexplored which the authors aim to envision and conceptualize.

This study employs a conceptual development approach to propose relationships among constructs, supported by 34 semi-structured consumer interviews.

This study defines AI credibility using source credibility theory (SCT). The conceptual framework of this study shows how perceived AI credibility positively affects four consumer-AI experiences: (1) data capture, (2) classification, (3) delegation, and (4) social interaction. Perceived justice is proposed to mediate this effect. Improved consumer-AI experiences can elicit favorable consumer outcomes toward AI-enabled offerings, such as the intention to share data, follow recommendations, delegate tasks, and interact more. Individual and contextual moderators limit the positive effect of perceived AI credibility on consumer-AI experiences.

This study contributes to the emerging research on AI credibility and consumer-AI experiences that may improve consumer-AI experiences. This study offers a comprehensive model with consequences, mechanism, and moderators to guide future research.

The authors guide marketers with ways to improve the four consumer-AI experiences by enhancing consumers' perceived AI credibility.

This study uses SCT to define AI credibility and takes a justice theory perspective to develop the conceptual framework.

Green consumption is fundamental to sustainable development, as it involves adopting practices and technologies that reduce the environmental impact of human activities. This study aims to analyze the influence of consumers’ green orientation on their environmental concerns and green purchase decisions. Furthermore, the study investigates the mediating role of consumers’ environmental concerns in the relationship between pro-sustainable orientation and green purchase decisions.

This study uses a quantitative methodology, applying the partial least squares method to a sample of 927 Portuguese consumers of green products. The sample was collected through an online survey.

Perceived benefits and perceived quality of products play a positive and significant role in influencing green behavior, especially when consumers are endowed with greater environmental concerns. In addition, consumers’ awareness of the prices of green products and their expectations regarding the future benefits of sustainable consumption positively impact green consumption behavior, further intensifying their environmental concerns.

According to the present findings, companies should adopt a holistic and integrated approach to promote green consumption. This means creating premium eco-friendly products, communicating their benefits, addressing the cost factor, emphasizing the future impact of eco-friendly options and raising consumers’ environmental awareness.

It is critical that environmental education is a priority in schools and that there are political incentives for green behaviors. In addition, media campaigns can be an important tool to raise awareness in society.

The results of this study provide important insights for companies on consumer engagement in the circular economy. Deepening knowledge of the antecedents of consumers’ environmental concerns contributes to a deeper understanding of green purchasing decision behavior, allowing companies to support new business strategies.

The aim of the present study was to contribute to the workplace diversity literature by experimentally manipulating gender expression through the use of makeup among women and men to determine makeup's impact on interpersonal discrimination in a real-world job selection context.

In an experimental field study, we applied either real (i.e. tinted) or placebo (i.e. transparent) cosmetic products to women and men confederate applicants. The women and men engaged in job inquiry and pre-interview conversations with store personnel in 136 retail stores across 3 shopping malls that were randomly assigned to one of 4 conditions in a 2 (confederate gender: women versus men) by 2 (cosmetic usage: real versus placebo) experimental design. The confederate applicants were accompanied by confederate observers and recorded interactions were later analyzed by naïve coders. The applicants, observers, and naïve coders rated interpersonal discrimination from store personnel in each interaction.

As hypothesized, women who enhanced their femininity through the use of makeup experienced significantly less interpersonal discrimination than women who did not. In contrast, there was no significant difference in interpersonal discrimination for men as a function of visual gender expression.

These findings highlight the pervasive gender norm expectations for women at work by examining gender non-conformity of women and men.

There is a growing mismatch between the skill demands of the industry and the offerings of academia. One way of reducing this mismatch is by improving collaborations between practitioners and instructors using web-networking platforms. However, it is important to understand practitioners’ considerations while collaborating with instructors. Therefore, this study identified these considerations in order to infer inputs for the design of the graphical user interface (GUI) of a web-based platform for connecting instructors and practitioners.

A mixed method was adopted through a survey and focus group. A survey was used to capture practitioners’ considerations while collaborating with instructors for student development, and a focus group helped uncover an in-depth understanding of the study phenomena. The data were analyzed using descriptive and inferential statistics and thematic analysis.

The results show the willingness of practitioners to collaborate with instructors for student development, the ways by which practitioners are willing to meet instructors' course-support needs and their considerations in deciding to do so. Slight differences were observed between the results of the survey and the focus group regarding the ranking of the practitioners’ considerations. The study highlighted demographic differences in practitioners’ considerations when deciding on meeting instructors' course-support needs. The results provide a basis to deduce the GUI inputs of web-networking platforms for connecting instructors and practitioners.

This study revealed practitioners’ design needs and GUI inputs to facilitate the design of web-networking platforms for connecting instructors and practitioners. This study also contributes to user interface design principles, theories on individual differences and practitioners’ involvement in student professional development.

The purpose of this paper is to study the relationship between board attributes and national culture on firms’ investment decisions.

The study used data from listed firms from seven Sub-Saharan Africa countries. Descriptive analysis was performed to provide the background statistics of the variables examined. This was followed by regression analysis, which constitutes the main data analysis.

The multiple regression analysis results indicate a negative relationship between uncertainty avoidance (UAI) and corporate investment decisions. The study also found that there is a negative relationship between the interaction between UAI and the number of independent board members and corporate investment decisions.

This study is one of the few to measure the influence of governance variables and national culture on corporate investment decisions in Sub-Sahara Africa.