Purpose This study aims to demonstrate and evaluate a structured three-stage rapid improvement event (RIE) methodology for diagnosing, implementing and sustaining operational improvements in manufacturing environments. A semi-automated electrical device manufacturing process is used as an illustrative case study to validate the approach. Design/methodology/approach The study applies a RIE structured around the three-stage Kaizen methodology (Pre-Kaizen, Kaizen, Post-Kaizen). The approach includes Gemba observation, process mapping, time studies, Yamazumi analysis, root cause analysis, rapid experimentation and immediate implementation of solutions. A cross-functional team executed the event over a short, intensive period to achieve fast, measurable improvements. Findings The implemented process improvements resulted in significant enhancements across various aspects of the production line. These improvements led to a more balanced workload between processes, highlighted by reduced cycle times and increased operator utilization. The average hourly throughput increased by over 40%, while the throughput per labor hour more than doubled. Additionally, reducing rejection rates from 6.34% to 1.3% and eliminating overtime expenses resulted in substantial cost savings. The optimization of labor utilization also led to significant annual savings in labor costs. These changes were implemented without job losses, with affected employees relocated to other positions as part of the company’s commitment to its workforce. Originality/value This study contributes to the literature by demonstrating the application of a structured three-stage RIE in a semi-automated manufacturing environment – an area with limited empirical evidence. By integrating Lean tools such as Gemba observation, Yamazumi analysis and Takt time evaluation within an RIE framework, the study provides a replicable model for achieving rapid, high-impact improvements without major capital investment. The findings offer new insights into how RIEs can effectively address performance issues in hybrid manual-automated processes.
Purpose This paper aims to explore the connections between green servant leadership (GSL), green human capital management (G-HCM) practices, green intellectual capital (GIC) and the environmental performance (EVP) of firms. Specifically, the mediating effect of G-HCM practices between GSL and GIC relationship, as well as the mediating effect of GIC on the G-HCM and EVP relationships were investigated. Design/methodology/approach Data were collected through a cross-sectional survey questionnaire from 203 rural banks in Indonesian banking sector. The study used partial least squares structural equation modeling to test the hypotheses. Findings The findings indicate that G-HCM practices act as a mediator between GSL and GIC. Furthermore, the research highlights that G-HCM practices, via its impact on GIC, indirectly influences EVP. The results confirm that all direct and indirect effects hypothesized in the study were supported. Research limitations/implications Findings are limited to rural banks; cross-industry samples are encouraged in future studies. Practical implications GSL and G-HCM practices must be enhanced by managers to improve GIC and EVP. Social implications The findings promote sustainable banking practices that contribute to environmental protection and ecological responsibility. Originality/value The study makes a meaningful contribution to advancing current theories by suggesting that the connection between G-HCM practices and environment performance is not solely determined by the additive effects of GSL and GIC nor by their interactive effects, but a combination of both.
Purpose This study aims to develop and empirically apply a structured framework for assessing Quality 4.0 (Q4.0) implementation maturity within manufacturing organizations. This study addresses the fragmented nature of existing Q4.0 assessment approaches by integrating strategic, organizational, operational, technological, analytical and customer-oriented dimensions into a unified hierarchical evaluation framework. Design/methodology/approach The proposed framework was developed through a structured review of prior Q4.0 and digital quality management literature and refined through expert consultation. The framework comprises 6 enablers, 18 criteria and 36 measurable attributes. A multi-grade fuzzy logic approach was used to aggregate expert evaluations and compute maturity indices. The framework was empirically applied within a large Saudi manufacturing organization operating in the food and beverage sector. Findings The empirical assessment classified the organization at the Advanced level of Q4.0 implementation maturity, with an overall maturity index of 7.2307. The findings of this study indicate relatively strong performance in leadership and strategic alignment, process integration and quality methodology and technology infrastructure and connectivity. In contrast, comparatively lower maturity levels were observed in data management and analytics, workforce readiness and customer-oriented digital integration. The results of this study further demonstrate that Q4.0 maturity depends on balanced development across interconnected organizational dimensions rather than isolated technological investment. Practical implications The framework provides managers with a structured diagnostic tool for evaluating current Q4.0 maturity and identifying priority areas for digital quality transformation. Originality/value This study contributes to the Q4.0 assessment literature by integrating the most consistently emphasized dimensions of digital quality transformation into a unified hierarchical assessment framework. This study further extends the application of multi-grade fuzzy logic to Q4.0 maturity assessment and provides empirical evidence from the Saudi manufacturing context, which remains comparatively underexplored in existing Q4.0 research.
Purpose This paper aims to develop and test a socio-economic framework that helps organisations balance exploitation and exploration through the conversion of qualitative dysfunction diagnoses into measurable key performance indicators (KPIs). Design/methodology/approach A five-stage intervention-research project grounded in the socio-economic approach to management (SEAM) was conducted in a mid-sized Lebanese manufacturing firm. Horizontal and vertical diagnoses generated 128 field-note quotes, which were combined with hidden-cost analysis to build a logframe mapping each dysfunction to exploitation or exploration activities. Findings The SEAM process produced a dashboard of 10 SMART KPIs that render the firm’s ambidexterity gap visible. Baseline measurement revealed US$219,600 in hidden costs distributed 86% exploitation and 14% exploration, signalling under-investment in future-oriented activities. After 3 months, human resources hidden costs fell 6.7% (US$11,411). Research limitations/implications Results were derived from a single case with a short horizon; longitudinal and multi-firm studies are needed to test generalisability. Practical implications This paper supplies a replicable five-step template such as negotiation, diagnosis, hidden-cost computation, KPI design, logframe monitoring, which can be used by practitioners to embed ambidexterity metrics into existing dashboards. Social implications By monetising hidden dysfunctions and pairing cost KPIs with innovation KPIs, the framework empowers employees as co-owners of performance data. Early gains in reduced absenteeism and training engagement suggest that transparent metrics can foster healthier workplaces. Originality/value This is the first study to fuse SEAM with organisational-ambidexterity measurement, converting qualitative dysfunction analysis into KPIs that simultaneously steer efficiency and innovation.
Purpose While equity crowdfunding (EC) has emerged as a transformative force in entrepreneurial finance, academic attention has largely centred on campaign-level factors, such as project quality and founder characteristics. In contrast, the platforms themselves – equity crowdfunding platforms (ECPs) – remain an overlooked yet critical component of the EC ecosystem. This study aims to address this significant gap by exploring how ECPs’ governance structures and digital visibility influence the success of fundraising campaigns. Design/methodology/approach The study adopts a quantitative approach, using a hand-collected data set of 801 EC campaigns launched between 2014 and 2022 on Italian ECPs registered with Commissione Nazionale per le Società e la Borsa. Logit regression models are used to assess the impact of board composition, gender diversity, female leadership and digital visibility on campaign success. Findings The results reveal that larger board size and greater gender diversity are positively associated with campaign success. In addition, digital visibility significantly enhances the likelihood of achieving funding goals. Practical implications The study underscores the strategic importance of strengthening internal governance, particularly through broad, gender-mixed boards and of enhancing digital visibility through Web presence, media coverage and search engine optimisation. Originality/value This study advances the literature on EC by shifting the unit of analysis from individual campaigns to the organisational characteristics of platforms. By introducing original variables, the paper contributes to a deeper understanding of how platforms reduce information asymmetries and enhance the fundraising performance of EC campaigns.
