Purpose The study aims to explore how the monitoring and resource provision function of board of directors impact the association between ownership concentration and small- and medium-sized enterprise (SME) initial public offering (IPO) underpricing in the context of an emerging economy like India. Design/methodology/approach The sample comprises 390 SME IPOs listed on Bombay Stock Exchange SME platform and National Stock Exchange EMERGE (EMERGE is the NSE new initiative for SMEs to raise the funds from investors) in India. To test the moderating impact of the board monitoring role and resource provision role, the study employs hierarchical moderated regression subject to the fulfillment of assumptions. Findings The findings divulge that ownership concentration significantly reduces underpricing, hinting towards the operationalization of alignment of interest hypothesis. With regards to moderating relationship, the study found that while board resource providing role negatively moderates the relationship between ownership concentration and SME IPO underpricing, board monitoring function fails to cast any significant impact on the relationship between ownership concentration and SME IPO underpricing. Research limitations/implications The present study ignores larger firms listed on the main platform which have complex decision-making than smaller firms. Besides, it is confined to only a single country, i.e. India. Extending the study to other countries with similar institutional characteristics would have validated the findings. Furthermore, the moderating impact of other organizational factors like firm age, lifecycle of firm and change in technology would form an interesting avenue for future research. Practical implications The findings of the study have practical implications for managers in designing the adequate board structure that significantly reduces underpricing. It thus further advices the issuers on focusing more on strengthening the resource provision role of board of directors for achieving higher rewards. The findings are helpful to policymakers in framing such policies that enhance the resource-oriented role of board of directors and resource accessibility for SMEs. Furthermore, the results advise the investors to be relatively assured about the SMEs whose board exercises its resource provision role emphatically. Accordingly, findings are helpful to investors in making investment decisions in alternative market settings characterized by the concentrated ownership structure. Originality/value The study furthers the debate on the importance of two prominent roles played by board as a moderating variable in the underexplored context of IPO underpricing of small and medium-sized firms in India.

Purpose The research paper’s purpose is to contribute to the literature by analysing the essential resources and processes required for successful commercialisation, the contemporary challenges and opportunities of artificial intelligence initiatives in Türkiye, and the diverse models and methods employed by these initiatives. Design/methodology/approach Within the scope of the research, interviews were conducted with 10 entrepreneurs who established artificial intelligence-oriented enterprises in technoparks in Istanbul and Antalya. All 10 interviews were analysed using the MAXQDA20 software tool. Structured qualitative content analysis was used for the data analysis procedure. Findings Based on the research, external factors have a significant impact on the future growth opportunities of the market. Expanding the client base, gaining international recognition, and securing financing are crucial for success. However, the findings reveal challenges in the relatively young local ecosystem. One major criticism is the lack of support in marketing and sales activities for refined products. To address this, providing financial incentives and knowledge transfer to those in need is vital. Research limitations/implications Since the research was conducted only with entrepreneurs who established and successfully commercialised artificial intelligence-oriented enterprises, it is recommended that future studies be performed with a widespread sample group, considering this limited situation. Furthermore, to overcome survivorship bias, it is recommended that posterior studies include failed commercialisation attempts in AI ventures. Practical implications It can be argued that there is no deliberate approach or model for commercialization. Entrepreneurs often draw from their own prior experiences or observe industry trends. Given the limited financial resources available in the domestic market and the challenge of attracting foreign investors to Turkish brands, entrepreneurs tend to rely on internal approaches for commercialisation. Originality/value This research delves into the commercialisation prospects and obstacles encountered by AI start-ups in Türkiye. It comprises qualitative insights into business models, commercialisation approaches, opportunities, and challenges. The data were obtained from interviews with entrepreneurs operating in the industry.

Purpose Building on the theory of resource-based view (RBV), this paper is determined to explore the key drivers that drive platform ecosystem adoption by small businesses and mediation mechanisms that facilitate the translation of these drivers into improved firm financial and nonfinancial performance. Design/methodology/approach In this study, structural equation modeling is used to analyze the data. A survey questionnaire was taken from 430 small businesses operating their businesses on various digital platform ecosystems in China to investigate the links between parameters by testing hypotheses. Digital startups operating their businesses on popular Chinese platform ecosystems, including Alibaba, Taobao, Jingdong, Maituan and HelloChe, were chosen. Findings The finding deciphers a nuanced interplay of the adoption drivers, with innovation capability emerging as a mediation mechanism translating these drivers into improved financial and non-financial performance. Research limitations/implications The acknowledgment of potential drawbacks, such as the focus on specific drivers of platform ecosystem adoption, highlights the need for future research to explore additional factors that may influence adoption decisions. By examining institutional factors, market conditions or external shocks like the COVID-19 pandemic, researchers can provide a more comprehensive understanding of the complexities surrounding platform ecosystem dynamics and offer insights into adaptive strategies for businesses facing uncertainty. Practical implications The outcome benefits policymakers and ecosystem designers by creating and overseeing platform ecosystems that support the highlighted drivers. This study further serves as a roadmap for both platform owners and prospective small enterprises as they map their path toward the digital frontier. Social implications The findings from the research indicate that small enterprises that embrace platform ecosystems can experience improved financial and non-financial performance, which in turn promotes economic development and the generation of jobs. By utilizing innovative strategies and maximizing their strategic advantages, these enterprises can not only prosper but also make significant contributions to community development and help alleviate joblessness. This highlights the significance of assisting with the incorporation of digital technology in small businesses to achieve wider societal advantages. Originality/value Research originality lies in bridging the gap between strategic inputs and measurable outcomes, stressing the vital function of a firm’s innovation in turning ecosystem-driven opportunities into enhanced performance. This means the pivotal role of this study lies in exploring platform ecosystem adoption drivers based on the theory of RBV and the way innovation capability of platform ecosystems facilitates the translation of these drivers into improved financial and nonfinancial performance.

Purpose Emergent leadership is a relatively new phenomenon, suggesting that leaders emerge from within teams without having a formal leadership assigned role. While emergent leadership has much relevance in today's organizations transitioning from vertical to horizontal leadership, there is a paucity of research about the process of emergent leadership that enables team members to become influential within teams. Design/methodology/approach Using purposive sampling, we interview 40 individuals in nine agile teams working in five Information Technology firms. Findings We identify various traits, experiences, behaviors, skills, and abilities of emergent leaders. Broadly, we conclude that an emergent leader serves as a “detail-oriented structure” or a “big picture coordinator.” Based on the findings, we propose a leadership emergence process that details how team members gain status and emerge as leaders, as well as the factors that can cause them to lose that status and return to becoming a regular team member. Furthermore, we introduce a model that demonstrates how technical expertise and personality traits interact, influencing team dynamics and facilitating the emergence of leaders within a team. Originality/value We contribute to the literature on emergent leadership by conceptualizing lateral influence and a leadership emergence process. We also extend the agile leadership literature and address some calls for empirical studies to understand the leadership dynamics in agile teams. We also show some limitations of the existing approaches and offer some useful insights.

Purpose The objective of this work is to demonstrate how the use of a business process management (BPM) methodology reinforced with the use of lean manufacturing (LM) tools and practices enhances information and documentation flows. Design/methodology/approach For this purpose, a case study on a large wind blade manufacturing company is described, in which BPM and LM were combined to improve information and documentation flows associated to the process of quality inspections and quality controls. Findings The joint use of BPM and LM strongly contributed to the improvement of information and documentation flows. The BPM lifecycle can be used to guide the entire improvement process, while LM tools can be used to act at specific points with an emphasis in the process analysis and implementation phases. Thus, LM complements a BPM approach leading to significant process improvements. Practical implications The results show that LM can be used to support some phases of the BPM lifecycle. Furthermore, LM can contribute to identify lean waste in information and documentation flows associated to quality management processes and help in the selection of methods and tools to support process improvements. Originality/value This study is one of the first reporting the use of LM tools and practices as complementary to the BPM methodology to support the improvement of information and documentation flows associated to quality management in a large manufacturing company. This research enriches the literature by presenting empirical evidence that these two continuous improvement approaches are not incompatible in their objectives and visions and can complement each other.

PurposeHow to embed artificial intelligence (AI) in human resource management (HRM) is one of the core challenges of digital HRM. Despite regulations demanding humans in the loop to ensure human oversight of AI-based decisions, it is still unknown how much decision-makers rely on information provided by AI and how this affects (personnel) selection quality.Design/methodology/approachThis paper presents an experimental study using vignettes of dashboard prototypes to investigate the effect of AI on decision-makers’ overreliance in personnel selection, particularly the impact of decision-makers’ information search behavior on selection quality.FindingsOur study revealed decision-makers’ tendency towards status quo bias when using an AI-based ranking system, meaning that they paid more attention to applicants that were ranked higher than those ranked lower. We identified three information search strategies that have different effects on selection quality: (1) homogeneous search coverage, (2) heterogeneous search coverage, and (3) no information search. The more applicants were searched equally often (i.e. homogeneous) as when certain applicants received more search views than others (i.e. heterogeneous) the higher the search intensity was, resulting in higher selection quality. No information search is characterized by low search intensity and low selection quality. Priming decision-makers towards carrying responsibility for their decisions or explaining potential AI shortcomings had no moderating effect on the relationship between search coverage and selection quality.Originality/valueOur study highlights the presence of status quo bias in personnel selection given AI-based applicant rankings, emphasizing the danger that decision-makers over-rely on AI-based recommendations.

Purpose This study investigates the factors that lead to the adoption of blockchain technology through payment transactions and how this not only affects real estate (RE) and blockchain transparency but also RE performance. Design/methodology/approach Data gathered across RE firms in the United Arab Emirates (UAE) were employed to test the model. The measurement model and structural equation modeling (SEM) were used to test the items and the hypotheses illustrated in the proposed model. Findings Perceived financial benefits, competitive pressure and top manager support were demonstrated to successfully influence blockchain adoption (BA). Despite blockchain’s early stages of development, its impact on RE operations cannot be ignored and should be more objectively examined in order to gain a better understanding of it. UAE blockchain-based companies could be seen as having a competitive advantage that maximizes resource consumption. Originality/value This study introduces the positive influence of blockchain technology on RE payment transactions and may advance information on how blockchain technology has the potential to change the RE sector. The paper finds its significance in exploring how RE payment systems must change to remain competitive in the market amid emerging digitalization trends.

Purpose The goal of this study is to better understand the driving force behind the use of artificial intelligence (AI) in pharmaceutical manufacturing firms (PMFs) that are recognized as developing countries in the Middle East and North Africa (MENA) region that are listed by the Chambers of the Industries of Jordan, the Kingdom of Saudi Arabia, Morocco, and Algeria. Furthermore, the effect of adopting and using AI in managing raw materials (RMs), products, parts, and components for PMFs through supply chains (SCs). Design/methodology/approach A self-administrated questionnaire survey was used to gather data from 95 out of 511 participating managers (e.g. manufacturing, supplying, IT, operational, and logistical managers) utilizing a quantitative technique with a random sample size. In fact, 18.8% of the 89 different manufacturing firms (MFs) in the MENA area responded, with five to six managers from each company. The raw data was analyzed using partial least squares structural equation modeling (PLS-SEM). Findings The study’s findings show that the readiness to embrace artificial intelligence (AI) in the production management supply chain performance (PMSCP) of pharmaceutical manufacturing firms in the Middle East and North Africa (MENA) is positively and significantly influenced directly and indirectly by sustainable strategic supplier reliability (SSSR), shipping process dependability (SPD), technological factors (TFs), and infrastructure transformational development capability (ITDC). Originality/value As the studied countries are growing economies, such study findings might offer insightful consequences for stakeholders and policymakers regarding the significance of using artificial intelligence system adoptions in pharmaceutical manufacturing enterprises in the MENA region. The managers may also concentrate on the strong positive direct and indirect links between SSSR, SPD, TFs, and ITDC preparedness to accept AI adoption and its applications and systems in supply chain and production management departments and the consequences of informational and product delivery.

Purpose This study assesses the current landscape of business continuity management (BCM) research while exploring research trends, structures and delineating potential future directions. Design/methodology/approach A comprehensive bibliometric analysis was conducted on 360 articles from the Scopus and Web of Science databases using Biblioshiny software. A meta-synthesis was employed to aggregate and synthesize findings from the bibliometric results. Findings The results demonstrate a notable increase in publication numbers since the onset of the pandemic, reaching a peak in 2022 with a total of 342 articles. A collaborative bond among scholars transcends geographical boundaries and national affiliations. The analytical results propose avenues for future research, addressing crucial areas such as the integration of business continuity management systems (BCMS), the development of BCM frameworks and a comparative analysis of business impact analysis (BIA) frameworks through pertinent theories. Research limitations/implications The study contributes theoretical and practical implications, serving as a valuable resource for academics and practitioners seeking to deepen their understanding of BCM’s role in business recovery and preserving organizational continuity in the face of disruptions. Originality/value This study pioneers a comprehensive approach by integrating bibliometric analysis and qualitative meta-synthesis, providing a consolidated overview of BCM research. Additionally, it presents future research proposals in this area.

PurposeThis work aims to integrate the concepts generated by a systematic literature review on patient flows in emergency departments (ED) to serve as a basis for developing a generic process model for ED.Design/methodology/approachA systematic literature review was conducted using PRISMA guidelines, considering Lean Healthcare interventions describing ED patients’ flows. The initial search found 141 articles and 18 were included in the systematic analysis. The literature analysis served as the basis for developing a generic process model for ED.FindingsED processes have been represented using different notations, such as value stream mapping and workflows. The main alternatives for starting events are arrival by ambulance or walk-in. The Manchester Triage Scale (MTS) was the most common protocol referred to in the literature. The most common end events are admission to a hospital, transfer to other facilities or admission to an ambulatory care system. The literature analysis allowed the development of a generic process model for emergency departments. Nevertheless, considering that several factors influence the process of an emergency department, such as pathologies, infrastructure, available teams and local regulations, modelling alternatives and challenges in each step of the process should be analysed according to the local context.Originality/valueA generic business process model was developed using BPMN that can be used by practitioners and researchers to reduce the effort in the initial stages of design or improvement projects. Moreover, it’s a first step toward the development of generalizable and replicable solutions for emergency departments.