This article aims to understand the challenges and key takeaways of implementing total quality management (TQM) in a virtual organisation.
An interventionist research (IVR) methodology combined with a qualitative critical event analysis was used to evaluate the challenges and concerns faced during the company’s adoption of TQM and understand the roles of the key players involved.
Standard process tools such as desktop procedures (DTP), focused teams, and service-level agreements (SLAs) were fundamental to implementing TQM in the company. These processes require the right leaders, but external agents may also be influential, acting as accelerators of change in adopting and using management practices in small companies. Indeed, the researcher acted as a problem solver, bringing innovative solutions to the firm using a hands-on iterative approach.
This research underscores the importance of critical success factors (CSF), such as employee engagement, training, and project management tools. These factors are not just important but crucial for the success of TQM in organisations seeking to adopt the industry’s best practices.
This study, conducted as a virtual IVR for TQM implementation, provides novel insights for practitioners and academics. It elucidates the pivotal role of some quality management tools in the journey towards TQM and the role of both internal and external critical players in the process, particularly in small virtual organisations based on innovative business models.
Many organizations currently transition towards digitalized process design, execution, control, assurance and improvement, and the purpose of this research is to empirically demonstrate how data-based operational excellence techniques are useful in digitalized environments by means of the optimization of a robotic process automation deployment.
An interpretive mixed-method case study approach comprising both secondary Lean Six Sigma (LSS) project data together with participant-as-observer archival observations is applied. A case report, comprising per DMAIC phase (1) the objectives, (2) the main deliverables, (3) the results and (4) the key actions leading to achieving the presented results is presented.
Key findings comprise (1) the importance of understanding how to acquire and prepare large system generated data and (2) the need for better large system-generated database validation mechanisms. Finally (3) the importance of process contextual understanding of the LSS project lead is emphasized, together with (4) the need for LSS foundational curriculum developments in order to be effective in digitalized environments.
This study provides a rich prescriptive demonstration of LSS methodology implementation for RPA deployment improvement, and is one of the few empirical demonstrations of LSS based problem solving methodology in industry 4.0 contexts.
This 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.
A 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.
ED 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.
A 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.
The study examines the role of ethical leadership in the innovative performance of employees. Further, the purpose of the study is to investigate the mediating effect of human capital and social capital on the relationship between ethical leadership and the innovative performance of employees.
The study collected primary data from 386 managerial-level employees of information technology (IT) companies in the northern region of India. Structural equation modelling (SEM) was used to analyse the data and derive the direct and indirect effects.
The findings indicate a significant positive impact of ethical leadership on the innovative performance of employees. Further, it was found that ethical leadership has both direct and indirect effects on the innovative performance of employees, where the indirect effect was mediated through intellectual capital (IC). The research confirms that IC and ethical leadership are crucial resources for fostering a knowledge-driven culture and innovative performance amongst employees.
The research has made a novel attempt to explore the interplay between ethical leadership, IC and innovative performance in the Indian context. Further, the study provides actionable strategies for business leaders to optimise business processes and encourage innovative practices amongst employees in the company.
By combining the notion of prospect theory with advanced machine learning algorithms, this study aims to predict whether financial institutions (FIs) adopt a reactive stance when they perceive climate change as a risk, consequently leading to the adoption of environmental, social and governance (ESG) practices to avoid this risk. Prospect theory assumes that decision-makers react quickly when decisions are framed as a risk or threat rather than as an opportunity.
We used a sample of 168 FIs across 27 countries and seven regions over the period 2003–2020. To conduct our empirical investigation, we compared the prediction accuracy of various machine learning algorithms.
Our findings suggest that out of 12 machine learning algorithms, AdaBoost, Gradient Boosting and XGBoost have the most precision in predicting whether FIs react to climate change risk in adopting ESG practices. This study also tested the overall climate change risk and risks associated with physical, opportunity and regulatory shocks of climate change. We observed that risks associated with physical and regulatory shocks significantly impact the adoption of ESG practices, supporting prospect theory predictions.
The insights of this study provide important implications for policymakers. Specifically, policymakers must take into account the risk posed by climate change in the corporate decision-making process, as it directly influences a firm’s adoption of corporate actions (ESG practices).
To the best of our knowledge, this is the first study to investigate the firm-level climate change risk and adoption of ESG practices from a prospect theory perspective using novel machine learning algorithms.
Big data capabilities have the potential to completely transform conventional methods of doing business. Nevertheless, the role of big data capabilities in fostering green marketing capabilities and improving green competitive advantage is still not fully understood. To add new knowledge, this paper aims to propose a moderated mediation model to strengthen green competitive advantage in a big data environment. The model introduces both the mediating role of green marketing capabilities and the moderating role of big data capabilities. We developed and empirically tested a moderated mediation model.
In this study, we have adopted a survey-based methodology. The study collected data from 337 managers and empirically analyzed it to test the theoretical model of moderated mediation. We employed structural equation modeling for empirical analysis.
The findings revealed that organizational learning improves green marketing capabilities, whereas the relationship between organizational learning and green competitive advantage is insignificant. The mediating role of green marketing capabilities in the relationship between organizational learning and green competitive advantage was statistically significant, indicating that green marketing capabilities serve as a bridge between organizational learning and green competitive advantage. Big data capabilities moderate the relationship between organizational learning and green marketing capabilities. The moderated mediation was also significant, highlighting that big data capabilities further strengthen the indirect effects of organizational learning on green competitive advantage via green marketing capabilities.
This paper delivers theoretical and practical understandings of the importance of organizational learning and big data capabilities. Similarly, it extends current knowledge and provides key insights for managerial decision-making.
This research focuses on analyzing the impact of Green Supply Chain Management (GSCM) on the Sustainable Performance (SP) of Spanish wineries, as well as the mediating effect of Green Ambidexterity Innovation (GAI) and the moderating role of Top Management Environmental Awareness (TMEA) on the main relationship posited (GSCM-SP). In addition, age, size and membership in a Protected Designation of Origin (PDO) were used to increase the precision of the cause-effect relationships examined.
The study proposes a conceptual model based on previous studies, which is tested using structural equations (PLS-SEM) with data collected from 196 Spanish wineries between September 2022 and January 2023.
The results of the research reveal the existence of a positive and significant relationship between the development of GSCM and SP of Spanish wineries, as well as the partial mediation of GAI and the positive moderation of TMEA in this linkage.
The novelty of this study lies in its exploratory approach, as it ventures into new research territory by examining the mediating effect of GAI and the moderating influence of TMEA on the relationship between GSCM and SP, being, to the authors' knowledge, the first research to investigate these specific dynamics.
Based on a quantitative investigation, this paper endeavors to examine Industry 4.0 (I4.0) adoption process by studying the impacts of absorptive capacity (AC) and innovative ambidexterity (exploration, exploitation), while also considering the moderating influence of learning capability (LC).
Data has been gathered through administering questionnaire to 468 managers representing 175 manufacturing firms. Subsequently, PLS-SEM technique has been employed to verify the research hypotheses.
Study findings reveal that AC is significantly associated with I4.0 adoption and innovation ambidexterity. However, innovation ambidexterity demonstrates partial (only exploration) significant association with the adoption of I4.0. Similarly, the findings indicate that LC acts as a partial moderator between innovation ambidexterity (exploration) and I4.0 adoption.
The study presents significant insights into I4.0 adoption process. The findings may support managers of manufacturing firms to understand and assess the influence of integrating contextual factors facilitating successful adoption of I4.0. The study emphasizes necessity of managers’ awareness regarding the importance of firm’s AC to transform smoothly to I4.0 technologies. In addition to, encouraging the innovation ambidexterity along with LC to enhance the adoption of I4.0.
While researchers demonstrate increasing interest in applying I4.0, concrete evidence to support the I4.0 adoption process is, still, insufficient due to ongoing challenges in digital transformation. Consequently, further research is needed, particularly in exploring how a firm’s ability to realize knowledge and foster innovation contributes to implementing I4.0. This paper seeks to tackle this lack of research by examining the connection between AC, innovation ambidexterity, and LC and the adoption of I4.0 in an emerging economy.
Electronic procurement has received primacy as one of the significant reforms to help fight corruption and inefficiencies in the public sector across countries. The purpose of this paper is to examine the effect of electronic procurement adoption on procurement performance. Additionally, the paper examines the moderating role of institutional quality in the relationship between electronic procurement and procurement performance.
The study applied an explanatory design and a quantitative research approach. Also, the study relied on UTAUT and institutional theory to develop a test research model using 121 responses from public entities in Ghana. Hypothesised paths were investigated using structural equation modelling.
The findings revealed that electronic procurement adoption positively and significantly affects procurement performance. Also, the findings indicated that institutional quality positively and significantly affects electronic procurement adoption and procurement performance, respectively. Lastly, the findings proved that institutional quality moderates the relationship between electronic procurement adoption and procurement performance.
The study focused on public procurement entities in the Greater Accra Region – Ghana. The study contributes to adopting electronic procurement, institutional quality, and procurement performance literature. The study also extends the UTAUT and the institutional theory to African public entities. The study reechoes the importance of institutional quality in developing economies to enhance electronic procurement adoption.
To the best of the researcher’s knowledge, this is the first study that examines the moderating role of institutional quality in the relationship between electronic procurement adoption and procurement performance.
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