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The study aims to evaluate the influence of capital structure decisions and asset structure on firms' performance for East African listed nonfinancial firms.

The research is descriptive and employs secondary data from the East African capital markets' websites. The generalized method of moments approach is used to estimate the relationship due to its ability to account for endogeneity problems.

The result shows that capital structure decisions and asset structure strongly influence the firms' performance. When long-term debts, short-term debts and tangible fixed assets increase, the return on total assets increases. An increase in the total debt ratio raises the return on equity (ROE). However, the increase in long-term debt lowers the ROE.

The results will help investors and potential investors decide on a financing policy that maximizes performance. Likewise, governments and other policymakers review the capital markets' frameworks to attract institutional and individual investors to the markets for financial availability and to increase profitability.

The research provides evidence on the influence of capital structure decisions and asset structure on firms' performance. Furthermore, its results contribute to firms' financing policy formulation and the corporate finance literature.

The coronavirus disease 2019 (COVID-19) pandemic has become a global humanitarian challenge. This scourge has impacted people from all walks of life as well as every economic sector and activity, from travel to automotives, hotels to banking, and supply chain to retail. The pandemic has affected not only physical and mental health but also financial health. Studies have examined the pandemic's economic impact, but very few have examined its impact on personal finances. Efforts to contain the pandemic's spread, such as lockdowns, have resulted in suspended business operations throughout the world that have intensified joblessness. To prepare and protect people from such unforeseen situations, financial education and planning are necessary. We attempt to expand the evidence on this issue by applying a structural equation modelling approach to identify the mediating role of financial literacy programs in preparing and protecting household wealth against sudden worldwide setbacks. The research design is descriptive and exploratory using snowball sampling technique. The data was collected through an internet survey. In total, 400 survey responses were obtained. After testing the measurement model for key validity dimensions, the hypothesised causal relationships are examined in several path models. The results indicated that coronavirus awareness exerts a direct or indirect influence on the financial health of individuals through financial literacy. We conclude that financial literacy has a full mediating effect on the personal finance of individuals during the COVID-19 pandemic. The findings not only contributed to the need and understanding of financial literacy but also have managerial implications. Financial literacy programs provide investment advice and suggestions which are actionable and also work to help individuals to come out stronger in terms of knowledge and skill set when the COVID-19 crisis passes.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.

Social media has made people better informed but also easier to manipulate. By using literature review and observing social media, the authors found a problem about echo chamber effect. The purpose of this paper is to know how the echo chamber affects the people who consume political news and the role of media diversity in it.

To conduct this study, the authors used a structured questionnaire on the Qualtrics platform to collect data from 183 participants. The authors collected data using a simple random technique. This study is based on the cross-sectional survey; the data collection period is from October to November 2023. The authors used the SPSS software to analyze the relationships between the variables and test the hypothesis.

This study found that, echo chamber is not affected by media diversity. Because of increased political interest, people will be less influenced by echo chambers. In addition, demographic factors affect political interest. People use search engines and social media sites instead of political websites when it comes to the consumption of political news online. People like to communicate with individuals who hold conflicting political views.

Researchers have not yet been able to gain a clear understanding of whether users are in an echo chamber or not and how they are interacting in that environment. Research on this topic is still going on from different perspectives. This study helped to clarify whether or not more media consumption will affect echo chambers. The possibility of being trapped in an echo chamber exists whether we use a single medium or a variety of media. The novelty of this study lies in the use of the echo chamber scale to investigate a thorough understanding of this word through the use of many factors.

Successful knowledge transfer (KT) between younger and older workers (YW and OW, respectively) is critical for organizational success, especially in light of the recent surge in employment volatility among the youngest and oldest segments of the workforce. Yet, practitioners and scholars alike continue to struggle with knowing how best to facilitate these exchanges. The qualitative study offers insight into this phenomenon by exploring how KT unfolds in YW/OW dyads.

The authors performed a reflexive thematic analysis of semistructured interviews with two samples of blue- and white-collar younger/older workers from the USA (N = 40), whereby the authors interpreted the “lived experiences” of these workers when engaged in interdependent tasks.

The analysis, informed by social exchange theory and exchange theories of aging, led to the development of the knowledge transfer process model in younger/older worker dyads (KT-YOD). The model illustrates that, through different combinations of competence and humility, KT success is experienced either directly (by workers weighing the perceived benefits versus costs of KT) and/or indirectly (through different bases of trust/distrust perceived within their dyads). Further, humility in dyads appears to be necessary for KT success, while competence was insufficient for realizing KT success, independently.

In exposing new inner workings of the KT process in YW/OW dyads, the study introduces the importance of humility and brings scholars and organizations a step closer toward realizing the benefits of age diversity in their workplaces.

Lean management is a suitable methodology for companies that want to improve their productive performance and competitiveness. This study aims to research levels of implementation and internalisation of Lean production tools in Spanish manufacturing companies, and explores differences in behaviour between SMEs and large companies based on data gathered over three time periods. The correlation between Lean adoption and company performance is also analysed.

Company survey data for the years 2012, 2015 and 2018 collected from 354 respondents were used to conduct a longitudinal study on the level of lean tool adoption and internalisation in manufacturing companies.

Over the years, the use of Lean tools has increased, whereas levels of internalisation have remained stable. Lean tool use in SMEs and large companies show significant differences in 2012 and 2015, but this is no longer the case 2018. Results also show that higher Lean tool use helps increase return on sales (ROS), and higher levels of internalisation of tools helps reduce the number of products rejected.

To date, there are no known studies on the use and internalisation of Lean tools or their correlations with business performance indicators in Spanish manufacturing companies.

The purpose of this paper is to structure existing research on knowledge management (KM) in small- and medium-sized enterprises (SMEs) to offer a comprehensive overview of research strands and topics in KM in SMEs to determine their evolution over time.

The paper, which is considered a follow-up literature review, is based on a systematic literature review that covers 180 scientific papers that were published since the review paper by Durst and Edvardsson in 2012 that covered 36 papers.

The findings of this review and those of the aforementioned review are brought together in the form of an overview that structures research on KM in SMEs based on themes that, in turn, allow the derivation of promising research directions and research questions aimed at structuring future research on KM in SMEs.

By combining the findings of this review with the findings from the review published in this journal in 2012, this paper offers, to the best of the authors’ knowledge, the most comprehensive literature review on KM in SMEs produced to date.

This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.

This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.

Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.

This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.