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This study investigates the antecedents of supply chain resilience of small and medium-sized enterprises (SMEs) and the effects of government assistance and disruption intensity in long-term disruptions.

This study collected data from 626 SMEs in Australia in 2022 and analysed data using partial least squares structural equation modelling.

The study empirically confirms that digital capabilities, prior experience in disruptions, supplier proximity and relationships are antecedents of supply chain resilience of SMEs, with supply chain robustness as a mediator. It further confirms that SMEs' access to government assistance positively moderates the relationship between digital capabilities and supply chain robustness. The disruption intensity moderates the relationships between supplier proximity and supply chain robustness with supply chain resilience. Severe disruptions weaken the effects of prior disruption experiences and supplier relationships on supply chain resilience.

The findings inform SME practitioners of the importance of building supply chain robustness, leveraging their prior experience, supplier proximity and relationships and capabilities and flexibility for dynamic supply chain structures when disruptions are intense.

The novelty of our study is the use of the Contingent Resource-Based View to understand the effects of firm and supply chain-level antecedents on supply chain robustness and resilience, considering the contextual contingencies of disruption intensity and government assistance. The focus on long-term disruptions extends the conventional supply chain resilience studies on supply and demand disruptions of small scale. We also explore the firm-level effects of government assistance, which extends the commonly tested economic-level effects. Furthermore, we investigate supply chain robustness and resilience as different but connected constructs, deviating from common approaches. The finding that the relationship between digital capabilities and supply chain robustness, not the relationship between digital capabilities and supply chain resilience, becomes stronger with higher access to government support shows the importance of this approach to investigating specific effects.

This paper aims to understand how government support initiatives can enhance the international performance of small and medium-sized enterprises (SMEs). To address the gap of literature, this paper employed three theoretical lenses to examine both of direct and indirect relationships between two main constructs.

This empirical study is based on data collected from Armenian exporter SMEs. The data collection utilized a random sampling approach, resulting in 138 fully completed questionnaires, yielding a response rate of 28.4%, comparable to previous studies in international business research. This sample includes firms from three main sectors: agriculture, manufacturing and services, reflecting the structure of Armenia's international trade. Relationships were examined using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results of this study indicate that government support initiatives lack a direct impact on international performance, while positing instead an indirect connection between the two constructs through strategic capability and institutional pressures.

The results of this study contribute to the international business literature in several ways. First, it surpasses the conventional examination of government support on firm performance by delving into both the direct and indirect relationships between these constructs. Second, it reveals that not all theoretical viewpoints hold equal strategic importance in explaining the internationalization of SMEs. From the practical point of view, findings help policymakers to maximize a country's export capacity by implementing tailored initiatives, considering the unique requirements of SMEs.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

This study aims to contribute to the understanding of Entrepreneurship and Resource-Based View (RBV) by investigating the research landscape of Innovation Determinants (ID). Through an extensive bibliometric analysis and knowledge mapping, we explore intellectual structures, emerging trends, research hotspots, and future prospects in the field from 1990 to December 2022. Additionally, we focus on identifying top research organizations, authors, collaboration patterns, and commonly used keywords to advance knowledge and awareness in this area.

A comprehensive retrieval strategy was employed to gather 2359 articles on ID from Web of Science, covering the period from 1990 to 2022. Utilizing CiteSpace as a visualization tool, we visually represent authors, institutions, and keywords. By examining knowledge maps using various indicators, we showcase the intellectual foundation and current research frontiers within the domain of ID.

Our findings reveal significant progress in academic research on ID over the past three decades, with a substantial number of 2359 published articles in the field. This signifies considerable advancement in exploring ID. The analysis of the co-authorship network presents a network of 406 authors represented as nodes and 112 collaborative interactions as links. The network's density indicates that only a minute 0.14% of the potential connections in the ID network have been established, highlighting the need for more cohesive and extensive global collaborations in this field.

This paper's originality lies in its temporal and dynamic examination of the past thirty years, utilizing CiteSpace for co-citation and co-occurrence network analysis. Additionally, the scientometric analysis reveals key co-occurring keywords, providing insights into the conceptual characteristics within the research field.

This research examines the long-held belief in the adaption-related literature that a firm’s ability to adapt organizational structure to changing environments is related to superior performance. We create and test a construct that reflects an organization’s ability to change structure, which we call Supply Chain Structural Adaptability (SCSA), rather than relying on proxies (e.g. structural form or organizational modularity) used in prior studies.

Quantitative data was collected from 218 firms to test our conceptual model.

We find that SCSA has a mixed effect on profitable growth under various environmental conditions.

We find evidence that refutes two widely held assumptions in organization research, namely, that structural form serves as a reasonable proxy for structural adaptability and that the benefits of adaptive capabilities always increase as environmental dynamism increases.

Because of growing corporate tax scandals, there is an enhanced focus on corporate taxation by governments, institutions and the general public. Transparency in tax matters has been identified as critical for effectively managing and promoting socially responsible tax behaviour. This study aims to explore the impact of ownership structure, board and audit committee characteristics on corporate tax responsibility (CTR) disclosure.

This research collected data from the annual reports of Pakistani-listed firms over 12 years, from 2009 to 2020. Consequently, the data set encompasses a total of 1,800 firm-year observations. This study uses regression analysis to test the relationship between corporate governance and CTR disclosure.

The results show that board gender diversity, managerial ownership and audit committee independence promote tax responsibility disclosure. In contrast, family board membership, CEO duality, foreign ownership and family ownership negatively impact tax responsibility disclosure. Additional analyses reveal the specific information categories that produce the overall effects on tax responsibility disclosure and assess the moderating impact of family firms on the governance and CTR disclosure nexus.

Corporations can use the results to encourage practices that enhance transparency and improve the quality of disclosures. Regulatory authorities can use the findings to stipulate better protocols. Doing so will be vital for developing countries such as Pakistan to improve tax revenue and cultivate economic growth.

While this research represents, to the best of the authors’ knowledge, one of the first empirical investigations of the association between corporate governance and CTR, the results contribute to the corporate governance literature and offer fresh insights into CTR, an emerging dimension of corporate social responsibility.

The purpose of this paper is to propose and validate a theoretical model to investigate the relationship between self-organisation, information integration, adaptability and supply chain agility in humanitarian organisations.

A theoretical model was developed from extant studies and assessed through a structured questionnaire survey of 86 humanitarian organisations operating in South Sudan. The data were analysed using partial least square structural equation modelling.

The study found that self-organisation has a discernible positive influence on supply chain agility not only directly but also indirectly through adaptability. Further, information integration does not significantly influence supply chain agility directly but is fully mediated by adaptability. Together, the antecedent variables account for 53.9% variance in supply chain agility.

This study contributes to providing an empirical understanding of a humanitarian supply chain as a complex adaptive system and hence the need to incorporate self-organising and adaptive dimensions in supply chain management practice. Furthermore, it confirms the centrality of the complex adaptive system feature of adaptability when building supply chain agility through self-organisation and information integration.

The findings provide a firm ground for managerial decisions on investment in self-organisation and information integration dimensions so as to enhance adaptability and improve supply chain agility in humanitarian organisations.

This study is distinctive in the sense that it uses the complex adaptive system variables to empirically validate the relationships between self-organisation, information integration, adaptability and supply chain agility in humanitarian organisations in the world’s youngest developing economy with a long history of conflict and humanitarian intervention. The mediating influence of adaptability examined in this study is also novel.

This article focusses on the hybrid strategy, a simultaneous combination of cost leadership and differentiation strategy. The study aims to examine the impact of hybrid strategy on firm performance through its anticipated positive effects on process and product innovation. In addition, we study the moderating role of adaptive capacity in the direct relationships of hybrid strategy with process and product innovation.

Structural equation modelling was used to analyse 1,842 Spanish firms with fewer than 250 employees. We randomly selected small and medium-sized enterprises (SMEs) operating in Spain from the Spanish Central Business Directory (2021) database. The overall sample design was based on stratified sampling.

We found that hybrid strategy is positively related to firm performance and to process and product innovation. Additionally, in firms implementing hybrid strategies, process innovation fostered firm performance. Finally, adaptive capacity strengthened the relationships of hybrid strategy with process and product innovation. This sheds light on how and when hybrid strategy is most effective in fostering SME performance.

We highlight that SMEs need to establish strategies that use diverse resources and capabilities and not just generate competitive advantage using one strategy (cost leadership or differentiation strategy). This requires an agile and flexible systems and structures.

Our research provides novel results by proposing the adoption of hybrid strategies instead of pure strategies (cost leadership and differentiation strategy) as a way for SMEs to survive during crises. Unlike “stuck in the middle” strategies, our study demonstrates the importance of hybrid strategies in a comprehensive model that links them to innovation and firm performance, with adaptive capacity being a determining factor.

This study aims to identify key research clusters (or sub-fields) in the field of performance measurement research, analyse its historical development and propose future research avenues.

Several bibliometric analysis methods, including co-citation analysis and text mining techniques, were used to review papers published on performance measurement research.

This study reveals eight main clusters of research in this field, ranging from theoretical-focused clusters (e.g. strategic performance measurement) to practical-focused clusters (e.g. design of performance measurement). These clusters are further categorised into four groups based on the size and degree of connectedness. Regarding the analysis of historical development, the established clusters, such as supply chain management, remain important, while newer clusters, such as hospitality and humanitarianism, have recently gained increasing interest.

This study applies citation-based clustering, a type of bibliometric literature review method that has been underused in the field of performance measurement. Moreover, the results obtained from this study are also distinct from those of previous studies, offering valuable insights especially for researchers. With a comprehensive understanding of the field, researchers can use it to understand the key literature, observe ongoing developments within their specialisation and inform their future research directions.

Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.

Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.

According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.

The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.

This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.