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This study aims to provide insights into different aspects of the extant literature on the effects of dividend announcements. Along with other outputs of a bibliometric study, this study provides deeper insights into the concentration of the extant literature and suggest future research agendas.

This study uses the bibliometric, network and content analysis of the dividend announcement literature indexed in Scopus. This study presents the temporal analysis, the network of authors, countries, author citations and the co-occurrence of author keywords. This study provides the concentration of the extant literature in three clusters and unearth some key future research areas. This study uses the latent Dirichlet allocation method for robustness.

A total of 54 documents examining the US sample have received 1,804 citations. Interestingly, the first article on emerging markets was published in 2002, when at least 34 articles on developed markets had already been published from 1982 to 2001. The content analysis of top-cited literature unveils diverse insights into dividend announcements’ effects on financial markets. Contagion effects negatively impact non-announcing banks, particularly larger ones. Dividend maintenance affects stock market momentum, influencing loser returns. While current dividend/earnings news may not predict future company performance, information content dominates bond market reactions to post-dividend announcements. Concomitantly, while financially constrained firms exhibit short-term gains but worse long-term performance following dividend increases, larger stock dividends send stronger market signals in China.

This study significantly contributes to the bibliometric and content analysis literature by analyzing the sample documents based on the sample examined. To the best of the authors’ knowledge, no previous bibliometric study in this domain has been conducted to explore the markets (developed and emerging) to which the samples examined belong and the quality of publications from developed and emerging markets.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Firms use design capability across the globe to compete and increase sales, e.g. Apple. However, the payoff from design know-how has been overlooked thus far. Academic research lags in this space despite the intersection of sales, technology and design in practice. This paper provides researchers and managers with implications of the interplay between design capability and technological market conditions to enhance a firm's sales.

Firms' capability design, and sales impact have been studied in this paper across different technological market conditions. Primary technological conditions of the industry under which firms operate are captured, which are technological intensity (TI), technological competitive intensity (TCI) and technological maturity (TM). Their interplay has been studied using panel data analysis, examining fixed and random effects.

Design is an important, interesting and non-imitable capacity that yields positive firm execution results. It provides an urgent differentiator and improves deal development. This study found that all four hypotheses are generally supported. The main finding is that, provided underlying technology is good, design significantly improves sales, but design alone cannot substitute for poor technology.

The results of this study link the three technological environment conditions, namely, TI, TCI and TM with sales growth. The authors find that design can and does add to superior performance, provided technological excellence exists prior. But, in the absence of good technology, design alone will hinder performance.

This paper examines the effect of firm design capability on sales growth. The paper finds a positive moderating effect of TCI and TM but a negative moderating effect of TI. The researchers believe these aspects of the design have not been studied before.

This study aims to provide insight into Library and Information Science (LIS) research in India using scientometric approaches. Web of Science (WoS) and SCOPUS databases were used for data retrieval. The study examines productivity in terms of source types, gender distribution, document formats, authorship and other factors. In addition, this study sought to identify trends or patterns in the research preferences of LIS scientists through text analysis.

Data were downloaded from the WoS and Scopus databases over 22 years and analysed using VOSviewer, Orange, Biblioshiny and CRExplorer softwares.

The findings reveal that 5,692 out of the 9,384 documents in both databases underwent the final examination. In total, 466 different sources produced all of those papers. Author analysis revealed that 6,603 different authors authored 5,692 documents. There were 4,209 male and 1,063 female authors. Furthermore, India shares maximum collaborations with the USA and England. The spectrogram features nine significant peaks corresponding to Lotka’s, Bradford’s and similar laws. Text analysis revealed that Indian LIS researchers have consistently investigated open access and digital or open libraries.

The findings of this study will provide readers with a better understanding of India’s contribution to LIS. In addition, the study will help academics identify research gaps and undiscovered areas in the Indian context that require further investigation.

Not many studies highlight Indian research trends and international collaboration in LIS. This study highlights research trends, collaboration and gender productivity in LIS. The most cited references and trending topics were also identified using reference publication year spectroscopy and text analysis techniques.

The coronavirus disease 2019 (COVID-19) pandemic adversely affected small and medium-sized enterprises (SMEs) in India. Amongst the challenges faced were the adjustments required in leadership skills to address pandemic-induced technological changes and the necessity for employee skill upgrading. This study examined the factors that influenced organisational performance in Indian SMEs, particularly in the context of the digital transformations that were brought about by the pandemic.

The study employed a cross-sectional design to investigate a set of hypotheses that were formulated to understand the relationships amongst digital leadership, digital training, empowerment and organisational performance. The data were collected during the pandemic from 487 employees who were working in various SMEs in India. Questionnaires were distributed through email and social media platforms, and electronic consent was obtained from each participant.

The study's findings indicated positive associations amongst digital leadership, digital training, empowerment and organisational performance. They also highlighted the mediating role of empowerment in these relationships. Furthermore, organisational resilience was found to positively moderate the relationship between empowerment and performance.

The study stands amongst the pioneers in exploring the role of digital leadership and digital training during the pandemic and their impact on employee empowerment amongst SMEs in a developing country.

This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.

Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.

Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.

The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.

The recent pandemic disrupted the way in which businesses transact with each other. In response to maintaining cleanliness in business-to-business (B2B) settings, artificial intelligence (AI)-enabled robots have been adopted as substitutes for cleaning personnel, yet their implications remain largely underexamined. This study aims to examine B2B buyer responses to cleaning information notices (human vs AI-enabled agent) placed at either the entry to the premises or the sales counter, thereby adding to the nascent literature in this line of inquiry.

Three field experiments were conducted across diverse B2B businesses (wholesalers in Studies 1–2 and a commercial business in Study 3). To achieve greater empirical rigor and generalizability, this research used diverse stimuli across different B2B settings. In addition, the results ruled out alternate explanations and shed light upon political ideology as a boundary condition. Finally, a single-paper meta-analysis confirmed H1, consolidating the established effect.

Featuring over 1,000 B2B buyers, the results show that politically liberal B2B buyers express greater preference for human over AI-performed cleaning while labor-orientated buyers are indifferent. Importantly, this effect is driven by greater relaxation associated with humans, which in turn, increases their future patronage and referral intent.

The results enrich the collective knowledge of the adoption of AI-enabled robots, reinforcing for marketing practitioners and businesses that the reliance on human-based outcomes remains a preferred touchpoint in B2B settings, particularly for liberals.

This study aims to examine the impact of the COVID-19 pandemic on knowledge-sharing drivers in small- and medium-sized family firms within the restaurant and fast-food industry. The pandemic has led to significant changes in business culture and consumer behaviour, accelerating digital transformation, disruptions in global supply chains and emerging new business opportunities. These changes have also influenced knowledge sharing (KS) and its underlying drivers.

To address the research objectives, a two-phase study was conducted. In the first phase, an exploratory analysis using the Delphi method was used to identify the essential drivers and factors of KS in family businesses (FBs). This phase aimed to establish a conceptual model for the study. In the second phase, confirmatory factor analysis was conducted to analyse the impact of the COVID-19 pandemic on the identified knowledge-sharing drivers. The study examined both the pre-pandemic and post-pandemic periods to capture the shifts in attitudes towards KS.

The findings indicate a significant shift in attitudes towards knowledge-sharing drivers. Before the pandemic, organisational drivers played a central role in KS. However, after the emergence of the pandemic, technological drivers became more prominent. This shift highlights the impact of the COVID-19 pandemic on KS within FB.

The research contributes to understanding knowledge-sharing in the context of FBs and sheds light on the specific effects of the COVID-19 pandemic on knowledge-sharing drivers. The insights gained from this study can inform strategies and practices aimed at enhancing KS in similar organisational settings.

The recent pandemic period (COVID-19), while negatively impacting many companies, has contributed to the growth and adoption of online platforms such as marketplaces and e-commerce. This environment has led many companies, which previously acted only through offline channels, to adopt new technologies and online channels and develop new e-commerce strategies. Small and micro enterprises are most vulnerable due to their limited resources and lack of capabilities. For this reason, the main objective of this paper is to unveil the e-commerce implementation capabilities that micro and small enterprises should build and the challenges they must face when managing an e-commerce strategy.

The authors adopted an inductive qualitative research design approach focused on multiple case studies. The firms operate in the food and beverage industry.

The findings identify several e-commerce implementation capabilities that micro and small enterprises operating in the food and beverage industry should build to manage e-commerce strategies. These are related to outsourcing management, multichannel management, time management, internal stock management and marketplace choice. Moreover, the paper identifies key e-commerce implementation challenges these firms must cope with. These regard distribution management, potential loss of control, fresh product management and lack of resources, time and capabilities.

This research shows that proper capacity management in the implementation of micro and small enterprises e-commerce strategies is critical to achieving efficient results and preventing challenges that threaten such strategies. The research offers guidelines and frameworks for micro and small enterprises to understand how to manage e-commerce and face its challenges.

This study aims to introduce an alternative model, “volatility, uncertainty, complexity and ambiguity (VUCA), Virtue and Vice” (3V’s), to unleash leadership skills, promote organisational collaborative change and impact sales performance during an unprecedented crisis.

The methodology outlines action research based on the 3V’s model and its application in an international business-to-business sales organisation during Covid-19. It explores alternative paths informed by play-at-work and Plato’s philosophy applied to work-based-learning. Each action/iteration adds to the model, which becomes more likely appropriate for various situations.

The 3V’s boosted change implementation and improved sales performance. The 3V’s conceptualised an invitation to immerse oneself in the constant “river of change” (VUCA) and a means of understanding the role of leadership in navigating this change by embracing simple rules: searching for justice (Virtue) and overcoming the barrier of public opinion (Vice).

The 3V’s model is grounded in leadership literature and a sole application, providing real international data relevant to organisations and leaders. This has yet to be evaluated further.

3V’s can enhance the understanding of a leading collaborative change and re-frame team dynamics in post-pandemic times for the broader public.

The approach advocated is a practice of “swimming alongside the team”, which should enable empowerment and collaboration rather than a top-down direction. Focussing on leaders who are moral people, this approach becomes a differentiator in a digital world.

This study examines Plato’s philosophy, play-at-work and other leadership theories in a model which prepares organisations to respond to crisis by providing the ability to reflect on human aspects and straightforward, transferable skills.