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This paper aims to assess the combined application of Lean Six Sigma and agile approach for optimizing operational processes of order management in the seed industry.

This study is based on an action research case conducted in a multinational Brazilian Seeds Business enterprise. This paper reports on the application of the Lean Six Sigma define-measure-analyze-improve-control (DMAIC), using the steps of DMAIC cycle as a sprint of agile approach. The methodology involves outlining an operational process through sequential activities, each associated with a cycle time, equivalent number of full-time employee and number of orders. Performance metrics for the order management process include continuous monitoring of these activities, using monitoring systems, management software and manual records to collect data.

The findings reveal significant improvements in critical-to-quality measures related to customer care, planning and logistics. The implementation of the DMAIC methodology and agile approach resulted in tangible enhancements in cycle time, defects per opportunities and overall process efficiency. The results allow the classification of defects, the identification of their causes and, consequently, the presentation of a control plan to mitigate these problems. Furthermore, the study identifies key causes of operational issues and proposes a prioritized action plan.

The limitation of this research is its restriction to a single case. The external validity of the results and generalizability to other organizational contexts may be compromised due to the lack of case diversity. The fact that the research focuses on a single company, even if it is a large multinational company, may limit the applicability of the findings to different sectors, sizes and organizational structures, which may be an opportunity for future research.

The findings suggest that the integrated approach of DMAIC and agile methodology contributes to a culture of continuous improvement and operational efficiency. The systematic collection and analysis of data enhance evidence-based decision-making, providing a robust foundation for strategic and operational choices. Moreover, the successful integration of methodologies presents a comprehensive framework applicable to diverse organizational challenges.

The paper applies action research to understand and address operational challenges, emphasizing practical solutions. The integration of DMAIC and agile enhances the depth of process analysis, enabling the identification, implementation and control of improvements. This study offers a significant contribution both to practitioners, providing practical implications, and to academics, enriching the Lean Six Sigma and agile body of knowledge.

This study is focused to support an ongoing development project of the case company's current state and the challenges of the order-to-cash (O2C) process. The O2C process is the most visible process to the customer, and therefore, its punctual and fluent order management is vital. It is observed that the high degree of manual work in the O2C process causes mistakes, delays and rework in the process. The purpose of this article is therefore to analyze the case company's current state of the O2C process as well as to identify the areas of development in this process by deploying the means of Lean Six Sigma tools such as value stream mapping (VSM).

The study was conducted as a mix of quantitative and qualitative analysis. Based on both the quantitative and qualitative data, a workshop on VSM was organized to analyze the current state of the O2C process of a case company, engaged in the energy and environment sector in Finland.

The results found that excessive manual work was highly connected to inadequate or incorrect data in pricing and invoicing activities, which resulted in canceled invoices. Canceled invoices are visible to the customer and have a negative impact on the customer experience. This study found that by improving the performance of the O2C process activities and improving communication among the internal and external stakeholders, the whole O2C process can perform more effectively and provide better customer value.

The O2C process is the most visible process to the customer and therefore its punctual and fluent order management is vital. To ensure that the O2C process is operating as desired, suitable process performance metrics need to be aligned and followed. The results gathered from the case company's data, questionnaire interviews, and the VSM workshop are all highlighted in this study. The main practical and managerial implications were to understand the real-time O2C process performance, which is necessary to ensure strong performance and enhance continuous improvement of the O2C process that leads to operational excellence and commercial competitiveness of the studied case company.

This article aims to examine whether the organizational changes brought about by digital transformation (DT) -such as a new organizational culture, new leadership and new business models-influence talent management, with the latter being seen as one of the major challenges facing companies in their process of digital transformation.

Using a quantitative methodology, a survey was applied to 314 companies in order to analyze the results of their talent management in the DT process. DT is not only digitalization as demonstrated in this study. Talent management is the key piece that can facilitate or block achieving high levels of digital maturity.

The study finds that the changes brought about by DT impact talent attraction, talent retention, and talent management in general, and also shows that digital transformation does not depend on digitalization, but rather that talent management is the key to either helping or preventing high levels of digital maturity being achieved.

The originality of this work lies in examining the influence of the changes that DT entails in talent management.

The purpose of our study is to investigate the impact of corporate culture on sales order backlog.

The authors use regression analysis to examine the relation between corporate culture and the level of sales order backlog, an important leading indicator of firm performance.

Using a large panel sample of US firms for the period of 2003–2021, the authors find a significant and positive relation, suggesting that firms with strong corporate culture have a higher level of sales order backlog.

The study findings contribute to two separate areas of research: corporate culture in management literature and sales order backlog in accounting literature. Prior study has focused on the impact of corporate culture on current firm performance. This study extends prior research by investigating the impact of corporate culture on order backlog, an important leading indicator of future performance.

The purpose of this paper is to explore a new grey relational analysis model to measure the coupling relationship between the indicators for the water environment status assessment. Meanwhile, the model deals with the problem that the changing of indicator order may result in the changing of the degree of grey relation.

The binary index submatrix of the sample matrix is given first. Then the product of the matrix and its own transpose is used to measure the characteristics of the index and the coupling relationship between the indicators. Thirdly, the grey relational coefficient is defined based on the matrix norm, and a grey coupling relational analysis model is proposed.

The paper provides a novel grey relational analysis model based on the norm of matrix. The properties, normalization, symmetry, relational order invariance to the multiplicative, are studied. The paper also shows that the model performs very well on the water environment status assessment in the eight cities along the Yangtze River.

The model in this paper has supplemented and improved the grey relational analysis theory for panel data.

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.

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.

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.

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.

The effects of the COVID-19 outbreak on the construction industry were formidable and far-reaching, as the construction sector is a major contributor to the gross domestic product (GDP), which balances various sectors of the global economy, and to infrastructure growth, which is a primary gauge of a nation’s advancement. The outbreak led to workforce disruptions, worker deficits, dwindling efficiency, elongated project durations, and scarce opportunities for training and mentorship, and despite endeavors to mitigate these challenges, construction timelines experienced significant interruptions. Various researchers have pinpointed contributing elements, but few have constructed a predictive model to gauge the degree of impact.

Therefore, this research intends to fill by introducing an ordinal logistic regression method to forecast the impacts of a pandemic or other similar type of crisis. To achieve this, an online survey was developed and distributed to collect the perceptions of the construction engineers and managers about the diverse contributors to the exceeding project timelines during the COVID-19 pandemic outbreak.

Findings from this study indicate that financial liquidity, modifications to original plans, delays in securing governmental clearances, and a shortage of competent labor have medium-to-high levels of impact on project schedules.

This study will furnish decision-makers with crucial knowledge that will give them the tools to refine their strategies and judiciously allocate resources to overcome the unique hurdles encountered by various construction segments and will enhance the industry's capability to respond more effectively to challenges inherent in this type of crisis.

The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.

Firstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.

The grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.

The example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM_2.5, PM₁₀ and O₃ are the main pollutants affecting air quality in northern Henan.

This paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix.

This paper explores how risks are managed in project practice beyond formalized risk management processes by applying the lens of actuality research to project risk management.

The paper follows a qualitative multimethod research approach utilizing literature review, interviews, observations and document analysis. The paper is based on three case studies and one interview study in project organizations facing green transition challenges.

Little work exists to reveal how risk management is actually done by project practitioners, and why. Few studies report on contextual variation and consider confounding factors beyond a “one size fits all” formalized explicit risk management process, despite ample evidence that risks are managed outside the formal process. The study documents that informal and/or implicit risk management activities add significantly more value.

The paper contributes a literature review of research into the actuality of project risk management, a sense-making framework of how risks are managed in practice beyond the formal, explicit risk-management process by including informal and/or implicit risk management activities, an empirical study of risk-management practice highlighting that informal and/or implicit risk-management activities dominate in practice, a discussion of why risks are managed outside formalized, explicit process and a research agenda to enable the design of impactful project risk-management practices.

The performance of large-scale projects is often challenged due to major environmental changes that occur during their life. However, literature has paid little attention to the governance adaptations required to respond effectively to these changes. This paper aims to study changes in the project environment over time, the corresponding governance adaptations and their impact on project performance.

To ensure triangulation between two sources of evidence, we used both primary and secondary data sources and examined 14 projects through 2 studies, the first focused on seven documented, illustrative case projects and the second on interviews with senior and project managers involved in seven additional projects.

We found the key environmental changes that should trigger appropriate governance adaptations to be market evolutions, technological advancements and sociopolitical events. However, we also found that these necessary governance adaptations are not commonly implemented timely, sufficiently or effectively.

The paper distills the dynamics of large-scale projects in achieving project effectiveness and raises theoretical propositions on the combination of environmental changes and deficient governance adaptations that, over time, turns efficient projects into ineffective projects and discusses implications for theory and practice.