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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.

The semantic relations between Arabic word representations were recognized and widely studied in theoretical studies in linguistics many centuries ago. Nonetheless, most of the previous research in automatic information retrieval (IR) focused on stem or root-based indexing, while lemmas and patterns are under-exploited. However, the authors believe that each of the four morphological levels encapsulates a part of the meaning of words. That is, the purpose is to aggregate these levels using more sophisticated approaches to reach the optimal combination which enhances IR.

The authors first compare the state-of-the art Arabic natural language processing (NLP) tools in IR. This allows to select the most accurate tool in each representation level i.e. developing four basic IR systems. Then, the authors compare two rank aggregation approaches which combine the results of these systems. The first approach is based on linear combination, while the second exploits classification-based meta-search.

Combining different word representation levels, consistently and significantly enhances IR results. The proposed classification-based approach outperforms linear combination and all the basic systems.

The work stands by a standard experimental comparative study which assesses several NLP tools and combining approaches on different test collections and IR models. Thus, it may be helpful for future research works to choose the most suitable tools and develop more sophisticated methods for handling the complexity of Arabic language.

The originality of the idea is to consider that the richness of Arabic is an exploitable characteristic and no more a challenging limit. Thus, the authors combine 4 different morphological levels for the first time in Arabic IR. This approach widely overtook previous research results.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0515

To study the strategic implications of TQM and TPM in an Indian manufacturing set‐up and to detail literature reviews to highlight gap areas. To examine the relationship between factors influencing the implementation of TQM and TPM and business performance for the following three approaches in an Indian context: TQM alone; TPM alone; both TQM and TPM together. This is done to extract significant factors for the above three approaches.

Empirical survey‐based research on a sample size of 108 manufacturing companies. Uses bivariate correlation and multiple regression analysis techniques to extract significant factors using SPSS.

The research identifies two sets of factors which are critical for the effectiveness of TQM and TPM: universally significant factors for all the three approaches like leadership, process management and strategic planning; and approach‐specific factors like equipment management and focus on customer satisfaction. The study also highlights the complexities involved in implementing TQM and TPM together.

The emphasis on extracted factors will help companies in realizing greater benefits through TQM and TPM. This study is equally important in a global context also, as companies across the globe are striving to achieve synergy of TQM and TPM.

The preparedness/status of Indian manufacturing industry for TQM and TPM implementation, as India is becoming a major sourcing base for the world and there is a paucity of such studies. The study of TQM and TPM in all the three modes simultaneously has not been investigated in the context of developing countries. Such studies are equally important in a global context.

Past research has shown that forecast combination typically improves demand forecast accuracy even when only two component forecasts are used; however, systematic bias in the component forecasts can reduce the effectiveness of combination. This study proposes a methodology for combining demand forecasts that are biased. Data from an actual manufacturing shop are used to develop the methodology and compare its accuracy with the accuracy of the standard approach of correcting for bias prior to combination. Results indicate that the proposed methodology outperforms the standard approach.

The purpose of this paper is to investigate the use of problem-solving approaches in maintenance cost management (MCM). In particular, the paper aims to examine characteristics of MCM models and to identify patterns for classification of problem-solving approaches.

This paper reflects an extensive and detailed literature survey of 68 (quantitative or qualitative) cost models within the scope of MCM published in the period from 1969 to 2013. The reviewed papers have been critically examined and classified based on implementing a morphological analysis which employs eight criteria and associated expressions. In addition, the survey identified two main perspectives of problem solving: first, synoptic/incremental and second, heuristics/meta-heuristics.

The literature survey revealed the patterns for classification of the MCM models, especially the characteristics of the models for problem-solving in association with the type of modeling, focus of purpose, extent and scope of application, and reaction and dynamics of parameters. Majority of the surveyed approaches is mathematical, respectively, synoptic. Incremental approaches are much less and only few are combined (i.e. synoptic and incremental). A set of features is identified for proper classification, selection, and coexistence of the two approaches.

This paper provides a basis for further study of heuristic and meta-heuristic approaches to problem-solving. Especially the coexistence of heuristic, synoptic, and incremental approaches needs to be further investigated.

The detected dominance of synoptic approaches in literature – especially in the case of specific application areas – contrasts to some extent to the needs of maintenance managers in practice. Hence the findings of this paper particularly address the need for further investigation on combining problem-solving approaches for improving planning, monitoring, and controlling phases of MCM. Continuous improvement of MCM, especially problem-solving and decision-making activities, is tailored to the use of maintenance knowledge assets. In particular, maintenance management systems and processes are knowledge driven. Thus, combining problem-solving approaches with knowledge management methods is of interest, especially for continuous learning from past experiences in MCM.

This paper provides a unique study of 68 problem-solving approaches in MCM, based on a morphological analysis. Hence suitable criteria and their expressions are provided. The paper reveals the opportunities for further interdisciplinary research in the maintenance cost life cycle.

The purpose of this study is to present a hybrid approach to model and predict long-term energy peak load using Bayesian and Holt–Winters (HW) exponential smoothing techniques.

Bayesian inference is administered by Markov chain Monte Carlo (MCMC) sampling techniques. Machine learning tools are used to calibrate the values of the HW model parameters. Hybridization is conducted to reduce modeling uncertainty. The technique is applied to real load data. Monthly peak load forecasts are calculated as weighted averages of HW and MCMC estimates. Mean absolute percentage error and the coefficient of determination (R²) indices are used to evaluate forecasts.

The developed hybrid methodology offers advantages over both individual combined techniques and reveals more accurate and impressive results with R² above 0.97. The new technique can be used to assist energy networks in planning and implementing production projects that can ensure access to reliable and modern energy services to meet the sustainable development goal in this sector.

This is original research.

The purpose of this paper is to present a novel modeling approach that combines a balanced systems engineering design model with a geospatial model to explore the complex interactions between natural hazards and engineered systems.

The approach taken in this work was to assemble a combined systems engineering design/geospatial model and interface it with a physics‐based hazard model to assess how to visualize the coupling of potential hazard effects from the physical domain into the functional/requirements domain.

It was demonstrated that it is possible to combine the two models and apply them to realistic hazard cases. A number of potential benefits are described and made possible by this approach including the generation of systems‐level damage assessments, the potential reduction of geo‐information data collection requirements, the incorporation of socio‐technical elements, the generation of functional templates, and the creation of a superior mitigation framework.

This approach offers a way to better understand natural hazard impacts on built systems, systemic effects of hazards, functional interdependencies between infrastructural elements, and a practical means to reduce geo‐information collection requirements.

The work is original in that it is the first time a balanced systems engineering design model has been made spatially aware and used to explore the impact of natural disasters on human systems. This work is valuable in that it directly addresses the shortcomings of spatial‐only approaches and could be used in data‐poor regions of the world.

Churn management is a fundamental process in firms to keep their customers. Therefore, predicting the customer’s churn is essential to facilitate such processes. The literature has introduced data mining approaches for this purpose. On the other hand, results indicate that performance of classification models increases by combining two or more techniques. The purpose of this paper is to propose a combined model based on clustering and ensemble classifiers.

Based on churn data set in Cell2Cell, single baseline classifiers, ensemble classifiers are used for comparisons. Specifically, self-organizing map (SOM) clustering technique, and four other classifier techniques including decision tree, artificial neural networks, support vector machine, and K-nearest neighbors were used. Moreover, for reduced dimensions of the features, principal component analysis (PCA) method was employed.

As results 14 models are compared with each other regarding accuracy, sensitivity, specification, F-measure, and AUC. The results showed that combination of SOM, PCA, and heterogeneous boosting achieved the best performance comparing with other classification models.

This study examined the performance of classifier ensembles in predicting customers churn. In particular, heterogeneous classifier ensembles such as bagging and boosting are compared.

Although benefits are promising, many companies face problems leveraging synergies between Lean and Digitalization at the program management level. This paper aims to identify activities to manage the boundaries of Lean and Digitalization programs.

The research design follows a cross-industry multiple-case study approach. A total of 14 interviews were conducted with Lean and Digitalization experts from 10 companies. Interview quotes were mapped on a pre-defined list of descriptive codes and iteratively merged and excluded.

We identified 12 activities by which companies manage the boundaries of their Lean and Digitalization programs. Three distinct boundary management approaches could be identified: collaborative, configurational, and competitive. A collaborative approach fosters governance, the belief in synergies, and the development of combined artifacts. A configurational approach creates combined responsibilities, assesses areas of collaboration, and fosters interaction across the organization. A competitive approach creates unclear responsibilities and exchange, perceives no added value in integration and follows separated implementation of Lean and Digitalization programs.

This study sheds light on the boundaries of Lean and Digitalization programs and identifies activities to manage them. We derive propositions for the Lean and Digitalization program management. Moreover, this study positions itself at the forefront of research investigating how integration of Lean and Digitalization actually occurs or does not occur.

The purpose of this chapter is to study the conceptual provisions of the theory of information economy and to determine its notion and essence.

The research methodology is based on the application of traditional methods of economic science, including the methods of systemic, problem, and comparative analysis, method of analysis of causal connections, systematization, classification, and formalization of scientific data.

The authors systematize the existing conceptual provisions of the theory of information economy and classify the conceptual approaches to its study as process approach, resulting approach, and combined approach; a comparative analysis of these approaches is also conducted.

The authors conclude that the evolutional development of modern socio-economic systems is dominated by the information economy concept, which should be the basis of the future developmental model of the global economic system. This concept develops within the combined approach, based on the previous concepts of digital economy and internet economy, which is a part of the process approach proclaiming technological capital, the key factor of reproduction, by focusing on the development of socio-economic systems and the concept of knowledge economy, which is a part of the resulting approach that emphasizes human capital and innovations as a target result of the development of economic systems. The information economy concept includes the features of previous concepts, emphasizes the importance of technological and human capital, applies information and communication technologies, and achieves results that are connected to highly effective creation, storage, distribution, and usage of information. It also supplemented them with a new sense of proclaiming information on the most valuable resources as well as provision of free and continuous interaction of economic subjects – the highest priority of socio-economic systems.