Abdul Rauf

This article investigates how artificial intelligence (AI) adoption could affect knowledge acquisition and frugal innovation (FI) associations to enhance a family firm's resilience. In Germany, family-owned small and medium-sized enterprises (SMEs) constitute the backbone of the economy, often characterised by long-term orientation, strong regional embeddedness, and conservative financing practices, which make them particularly relevant for studying resilience under technological disruption. A framework for this study is proposed and tested by integrating effectuation logic and the Diffusion of Innovations (DOI) theory. This research used a quantitative research technique and structural equation modelling, using data from family-run, SMEs in Germany, which account for a large share of employment and a significant portion of innovation activity in the Mittelstand context. The study employs time-lagged data to capture these dynamics. The study posits that AI adoption (AIA) has a crucial moderating function, and FI acts as a mediator in explaining organisational resilience (OR). This research combines effectuation logic and the DOI theory to answer the contradiction between augmentation and automation. The second contribution pertains to FI and its role in the nomological network involving AIA and OR. Third, this study advances methodological rigour in family firm research by applying a time-lagged SEM design, thereby contributing evidence from the comparatively underexplored context of German family SMEs.

Drawing on the latest extension of the Uppsala process model, this study examines how unicorn companies can utilize big data analytics capabilities for rapid internationalization through the digital transformation and digital innovation process. Data were collected using a German‐translated survey, which employed a snowball sampling approach. Three procedures were employed to ensure the quality, precision, and suitability of the terminology during the development and translation of the questionnaire, thereby guaranteeing content validity. The list of unicorn SMEs was compiled for start‐up businesses valued at over $1 billion. The Smart Partial Least Squares (PLS) 4.1.1.5 software, used for structural equation modeling (SEM), was employed for measurement model development and hypothesis testing. The Statistical Package for the Social Sciences (SPSS) 22 software was used for descriptive and correlation analysis, as well as to analyze the artificial neural network (ANN) dataset. The study found a significant positive relationship between Big Data Analytics Capability (BDAC) and Digital Transformation (DT), as well as between DT and Digital Innovation (DI). A unique serial mediation pathway is proposed, leading to unicorns' rapid internationalization, where DT and DI serially mediate between BDAC and the scope of internationalization. This study also confirmed that knowledge stock moderates and strengthens the impact of BDAC on DT. Regarding ANN, we have unique findings and have compared them with SEM.

This study examines the influence of Systematic Strategic Planning (SSP) on the Sustainable Performance (SP) of manufacturing Small and Medium Enterprises (SMEs) in Pakistan. Despite SMEs’ vital contribution to economic growth, there is limited empirical research on how strategic planning enhances sustainable performance in SMEs operating in emerging economies facing political and economic instability. Drawing on the Triple Bottom Line (TBL) and Resource-Based View (RBV) theories, this study investigates the mediating roles of Strategic Intent (SI) and Strategic Formulation (SF) in the SSP-SP relationship. A quantitative research design was employed, and data were collected through structured questionnaires distributed to senior executives and decision-makers of manufacturing SMEs. A total of 410 valid responses were received. Structural Equation Modeling (SEM) was applied using AMOS 28 software to analyze the data and test the hypothesized relationships. The results demonstrate that SSP has a significant direct effect on SP and an indirect effect through SI and SF. Specifically, the components of SSP—strategic analysis, strategy creation, strategy execution, and monitoring and evaluation—enhance SMEs’ economic, environmental, and social performance. The study highlights that adopting systematic strategic planning practices enables SMEs to navigate complex and uncertain environments, achieve competitive advantage, and contribute to sustainable development goals. This research fills a critical gap in the literature by focusing on manufacturing SMEs in Pakistan, an under-researched context in the sustainability and strategic management fields. It offers practical insights for SME managers and policymakers to develop and implement comprehensive strategic planning frameworks that foster sustainability. The study also provides theoretical contributions by integrating SI and SF as key mediators within the TBL and RBV theoretical frameworks.

This paper explores the impact of integrating human factors—such as ergonomics and employee involvement—with technological innovations on manufacturing performance, sustainability, and productivity. It develops a holistic framework that organizations can adopt to achieve world-class manufacturing excellence, emphasizing the synergistic relationship between human factors and technological advancements, and highlighting their combined effect on fostering operational improvements and sustainability. The research adopts a robust quantitative approach, utilizing comprehensive surveys to analyze the individual and combined effects of human factors and technological innovation on manufacturing outcomes. The methodology involves data-driven analysis supported by statistical models, ensuring a rigorous examination of the relationships between variables. The findings show that integrating human factors with technological innovations significantly enhances both industrial production levels and operational efficiency, underscoring the importance of this integration for promoting sustainable manufacturing processes and maintaining competitiveness in the face of rapid technological changes. One key limitation of this research is the generalizability of findings across diverse industry contexts, as the pace of technological evolution and the emergence of new technologies may affect the applicability of the proposed framework. Future studies should investigate the evolving nature of human–technology integration in various sectors. The paper provides practical strategies for manufacturing managers and policymakers to employ when integrating human factors with technological innovations, outlining a strategic implementation framework aimed at improving manufacturing performance, fostering innovation, and ensuring a competitive edge within the dynamic context of Industry 4.0. This research contributes to the existing literature by offering a comprehensive, synergistic approach to the integration of human factors and technological innovation, providing valuable insights for industry practitioners seeking to implement sustainable manufacturing practices and achieve operational excellence.

This paper aims to generate a clear understanding of Pakistan’s important attributes and their direct and indirect influence via perceived destination images on international tourists’ intentions to visit for a holiday. It employed quantitative research methods through the use of a correlation research design. Both direct and indirect effects of destination attributes on visit intentions were examined and a self-administered online survey was distributed across several social media platforms. The results of multiple regression analysis revealed that landscape, services, local attitudes toward tourists, safety and risk, sport and special events were found to be statistically significant predictors of such intentions. However, all the destination attributes were found to have an indirect influence on international tourists via the perceived destination image of Pakistan.