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The study investigates factors like media, tribal, religious and party politics' influence on Nigerias’ 2023 presidential election choice. It confirms dominant social media platforms and examines their influence on election polls, e-participation and political candidate choice. The main objectives of this study are to: investigate if tribal, religious and party politics affect the respondent’s choice of a presidential candidate, ascertain the respondent's most used social media platform for political engagement and determine how social media platforms influenced the election polls during the 2023 Nigerian presidential election.

A sample size of 384 registered voters was used to survey three states in Southeast Nigeria hinged on the technological acceptance model, the instrumentalist theory of ethnicity and the theory of reasoned action.

The study found that tribal politics did not influence political candidates during the 2023 Nigerian presidential election. However, religious and party politics influenced their choices as well as X (Twitter), found as the most used and most influential social media platform vital for enhancing participatory democracy and informing people at real-time.

The researchers experienced challenges such as ensuring that the respondents filled the questions appropriately to reduce the number of void questionnaires and a funding problem since they had yet to receive any grant to enhance the study.

The study commends improved Internet connectivity and accessibility among the citizens for increased political engagement on social media. It also recommends that the Nigerian government enforce the rule of law in politics to enable diverse tribes and religions to experience democratic e-participation and development without marginalisation or subjugation by incumbent power. The findings affirm that social media is apt in political communication during the 2023 presidential elections in Nigeria. The study is a contribution to knowledge, timely and original.

An ever-increasing number of companies outsource logistics activities to third-party logistics (3PL) providers to beat the competition. From the buyer's (shippers') perspective, selecting the right 3PL provider is crucial, and from the 3PL provider's perspective, it is imperative to be attractive and to retain clients. To this aim, a potential lever can be physical assets, such as warehouses, which the literature has traditionally neglected. The objective is to benchmark the importance of warehouses for 3PL providers to attract/retain clients and for shippers to select the right 3PL provider.

The authors performed an empirical investigation through interviews on dyads (3PL providers/shippers) and utilized the Best-Worst Method (BWM) to rank the criteria used in the 3PL buying process and allow the warehouse's role to emerge.

Results show that the 3PL buying process consists of four phases and three evaluation steps. The selection criteria are classified into three groups: order qualifiers, order winners and retention factors. The warehouse has different levels of importance throughout the process. It appears that it can indirectly enhance the attractiveness and retention capability of 3PL providers through other selection criteria.

By combining the resource-based view and the customer value theory, this research extends the theory on logistics outsourcing by studying the phases of the 3PL buying process and scrutinizing the criteria used in different evaluation steps. The research adds a double perspective of analysis (3PL providers and shippers), which is missing in the literature, and focuses on the importance of warehouses.

Social media is replete with malicious and unempathetic rhetoric yet few studies explain why these emotions are publicly dispersed. The purpose of the study is to investigate how the intergroup counter-empathic response called schadenfreude originates and how it prompts media consumption and engagement.

The study consists of two field surveys of 635 in-group members of two professional sports teams and 300 residents of California and Texas with political party affiliations. The analysis uses SEM quantitative methods.

Domain passion and group identification together determine the harmonious/obsessive tendencies of passion for an activity and explain the schadenfreude response toward the rival out-group. Group identification is a stronger driver of obsessive passion compared to harmonious passion. Schadenfreude directly influences the use of traditional media (TV, radio, domain websites), it triggers social media engagement (posting), and it accelerates harmonious passion's effects on social media posting.

The study is limited by the groups used to evaluate the research model, sports, and politics.

The more highly identified and passionate group members experience greater counter-empathy toward a rival. At extreme levels of group identification, obsessive passion increases at an increasing rate and may characterize extremism. Harboring feelings of schadenfreude toward the out-group prompts those with harmonious passion for an activity to more frequently engage on social media in unempathetic ways.

This study links the unempathetic, yet common emotion of schadenfreude with passion, intergroup dynamics, and media behavior.

Considering the detrimental impact of workplace cyberbullying on employees and organizations, it is necessary to understand factors that potentially induce employees to engage in cyberbullying and to recognize personal characteristics that may help employees mitigate its impact. This research applies the conservation of resources (COR) theory to investigate the effect of organizational politics and political skill on employees' exposure to workplace cyberbullying as well as to analyze the subsequent impact on emotional exhaustion. Moreover, the interaction effect of political skill and organizational politics on employees' exposure to workplace cyberbullying is analyzed.

The total of 358 complete questionnaires were obtained from one medium-sized public university in Thailand. The partial least squares structural equation modeling (PLS-SEM) was used to analyze the data.

The analysis supports the positive association between organizational politics and employees' exposure to workplace cyberbullying. Employees' exposure to workplace cyberbullying also has a positive association with emotional exhaustion. On the other hand, the analysis showed that political skill has a negative association with employees' exposure to workplace cyberbullying. The result from the moderating effect analysis further shows that political skill also reduces the impact of organizational politics on employees' exposure to workplace cyberbullying.

The incorporation of the COR theory provides theoretical insight into how political skill of employees can buffer the impact of organizational politics on exposure to workplace cyberbullying. It advances the knowledge found in previous research that lacked solid theory to explain the interaction between organizational politics and political skill of employees in the area of workplace cyberbullying.

Organizations use innovations and respond to external pressures, creating a transition to the sociotechnical system. In their transitions, they interact with the environment and undergo adaptation-selection. The extant literature used a multilevel perspective (MLP) with a structural view and examined dynamics and transitions (phenomena) in a noninterventionistic setting. This study aims to examine the dynamics and phenomena with a microstructural or functional view and expand the MLP; this paper uses neo-institutionalism and human values as part of the functional view. Moreover, when the authors examine the phenomena in an interventionistic setting, they can obtain certain unique dynamics and their influence on the phenomena.

The authors need to examine the phenomena in its setting, so this paper selected a case study, Indian electricity generation. For diverse heuristic and analytic views, it selected two Indian states.

The findings from the functional view showed that organizations exhibit certain traits of neo-institutionalism and human values, which mediate their responses (behavior) to external pressures. Additionally, due to the interventionist state, their dynamics use shaping instead of selection logic for innovations, which decides the transition pathway selection (technology adoption). It further decided the extent to which innovations cumulate as stable designs. As a result, the responses and the transition provide benefits in the short term while invariably failing in the long term.

By selecting cases with higher investments in renewable energies and combustible fuels, the authors can expand the functional view to include user typologies such as producers, intermediaries and citizen groups and obtain further insights into transitions.

The study highlights the generation dynamics specific to Indian electricity generation and its transition pathways. The study’s outcome provides insights to researchers and practitioners in formulating policy changes and transforming electricity generation.

The study uses a functional view comprising neo-institutionalism and human values and expands the sociotechnical transition theory. In addition, selecting an interventionist setting provided insights into dynamics specific to organizational behavior and associated services. Finally, the obtained insights offer suggestions for technology development to better manage transitions with adaptation-selection.

There is a growing worry about people possibly isolating themselves in online bubbles and avoiding contact with ideas that differ from their beliefs, creating a scenario of ideological polarization. To investigate into this matter, this work aims for a reflection about the contingency of communication in social media. Does social media make the experience of communication in the digital space more contingent (providing it with more possibilities, with people accessing different contents and ideas) or less contingent (reducing the available possibilities, making people isolate themselves)?

This is a theoretical work, constructed through bibliographical reviews. To reflect about the question that are posed, the author selected Niklas Luhmann's social systems theory to approach the concept of contingency. In addition to that, the author presented the main arguments of the debates about echo chambers and online bubbles. In the end, the author combined the two reviews together using elements of the Luhmannian theory and drew some conclusions about the initial question.

The study concluded that social media have an ambivalent potential regarding contingency in the digital space: it can both expand or reduce the available possibilities of communication, depending on criteria like topic, potential of diffusion and focus of attention. There is no one-side effect.

The approach at echo chambers does not reflect “the” form of contingency in social media, but “a” form. Therefore, the study cannot provide any general conclusions about the relation between contingency and social media. The digital space is a large one, and more studies are required to achieve more substantial propositions.

The research has an originality value both for systems theory and social media studies. First, because, as far as the author knows, no other system-theoretical argument has taken the connection between contingency and social media as a primary analysis object. Second, because of a theoretical interpretation effort, the studies of echo chambers indicate mixed results about the phenomenon of online isolation, but no attempt was made to make sense of these mixed results from a specific sociological theory. The author did that by using Luhmann's theoretical framework, which proved to be a good tool for explaining and unifying these different results on a more abstract level.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

The purpose of this study is to explore the roles that sociocultural systems such as traditions, religious practices, and rituals play in upholding gender imbalance in Fiji.

This qualitative study relies on results from semi-structured interviews with auditors, educationalists, academics, partners from leading accounting/audit firms, company directors and high-ranked government officers. Thematic analysis was conducted both manually and using MAXQDA software, and the themes that emerged from both analyses are complementary. A few more complementary analyses were also conducted such as Word Cloud.

The results support the claim that the religious traditions and rituals are strongly linked to gender-inequitable beliefs and suggest sociocultural factors impose on women experiencing self-effacing emotions and passive acceptance of lower status, contributing to the persistence of gender inequality. It also emphasizes the need to challenge certain sociocultural practices to promote greater gender equality, which is the theme emerged from thematic analysis. Additionally, this paper proposes four distinct types of attitudes in this regard as self-effacing feminist, self-effacing traditional, self-effacing modesty and talented driven.

Respondents' openness authenticity may be limited by factors like selection bias, small sample size and other potential constraints in this study.

The findings might influence stakeholders to advocate for policy changes to promote women's representation in leadership positions. The results give voice to various segments of society who are advocating greater gender diversity on board representation in Fiji. The themes immerged and theories developed would make a substantial contribution to the existing literature.

The findings highlight the importance of addressing gender inequality in leadership positions to promote inclusive and sustainable growth.

This study sheds light on the less-explored domain of internal barriers to gender equality within Fiji. It adds a novel dimension to the understanding of how cultural norms intersect with individual perceptions to shape gender inequality.

The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of computer science education.

This study adopted the quasi-experimental design to determine the efficacy of the CTCA in breaking difficulties related to the study of spreadsheets as a difficult concept in the Nigerian computer science education curriculum. Junior high school students studying computer science education participated in the study. The control group had 30 students, with 35 students in the experimental group. The experimental group was taught using CTCA, while the control group used the lecture method. The spread sheet achievement test, which had 40 items on spreadsheet, was used to collect data.

The results showed that the experimental group significantly outperformed the control group [F (1,60) = 41.89; p < 0.05]. The findings showed the potential of CTCA in improving students' performance in spreadsheets in the computer science education curriculum.

The originality of this study is hinged on its ground-breaking test of the CTCA to the study of the spreadsheet. The findings of this study indicate its efficacy in improving students' understanding of spreadsheet and computer science education.

Structural mentoring barriers are policies, practices and cultural norms that collectively disadvantage marginalized groups and perpetuate disparities in mentoring. This study aims to better understand structural mentoring barriers at the postdoctoral training stage, which has a direct impact on faculty diversity and national efforts to retain underrepresented groups in research careers.

A diverse sample of postdoctoral scholars (“postdocs”) from across the USA were asked to participate in focus groups to discuss their training experiences. The authors conducted five 90-min focus groups with 32 biomedical postdocs, including 20 (63%) women and 15 (47%) individuals from underrepresented racial/ethnic groups (URG).

A social-ecological framework was used to categorize both the upstream and downstream manifestations of structural mentoring barriers, as well as mentoring barriers, overall. Notable structural barriers included: academic politics and scientific hierarchy; inequalities resulting from mentor prestige; the (over) reliance on one mentor; the lack of formal training for academic and non-academic careers; and the lack of institutional diversity and institutional mentor training. To overcome these barriers, postdocs strongly encouraged developing a network or team of mentors and recommended institutional interventions that create more comprehensive professional development, mentorship and belonging.

For postdoctoral scientists, structural mentoring barriers can permeate down to institutional, interpersonal and individual levels, impeding a successful transition to an independent research career. This work provides strong evidence for promoting mentorship networks and cultivating a “mentoring milieu” that fosters a supportive community and a strong culture of mentorship at all levels.