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Problem-solving, systems thinking and design thinking are disciplines practiced by all human beings and is also innate in other living objects with limited use of symbolic structures. They are necessary to achieve the goals and survive. Interpretation of problem-solving as a change in equilibrium makes it applicable throughout the inanimate world. The aim is to describe the proposed empirical systems theory that integrates problem-solving and systems thinking through design thinking.

A brief historical background describes why comprehensive empirical systems theory has not been attempted before except as a restricted version in engineering systems. The methodology of the general theory follows that of conventional science, but with systemic content. Interference by required mental or physical product/systems changes states which is subject to discussion, creativity, innovation and inspiration accomplished by iteration as necessary.

A problem-solving structure has been created, which is implemented in a methodical way to aid the innate ability of individuals and organisations, and is open to modifications and the use of quantitative methods. Processed natural language allows for implementation at the operational level.

The proposed systems theory is an empirical theory that uses the structural properties of parts of the world. The integration makes “systems” the driver of change of state and offers fundamental concepts. The implementation shown in Figure 2 is methodical and can be applied by individuals and organisations subject to peer review and development. The method clarifies the roles of product/artifact and systems designers.

The purpose of this study is to improve the magnetron quality in Company T by identifying the nonconforming defect, adjusting the factors affecting the leakage of the magnetron tube core, and determining the optimal parameter values of these factors.

A case study method is used to present the quality improvement of magnetron tube core. The define, measure, analyze, improve, and control framework is applied in the case study as well as several Six Sigma tools.

The results show that Ag–W thickness, Ag–W installation state and furnace entry interval are significant factors on the leakage of magnetron tube core, and the optimum settings for these factors are 0.055 mm, offset by 1 mm from the outer edge and 5 cm, respectively.

The main limitation of this study is that it was carried out on a small number of production processes. The authors would like to analyze more case studies on the improvements of after-sales quality and supplier quality.

This research could be used in magnetron manufacturing process as a tool for managers and engineers to improve product quality, which can also be extended to similar manufacturing systems.

In this case study, the Six Sigma approach has been applied for the first time to solve magnetron manufacturing problems by improving the quality of magnetron production process. It can help the quality engineers be more familiar with the deployment of Six Sigma and effective tools.

Recent trends in total quality management (TQM) argue in favor of incorporating environmental concerns into TQM and considering external stakeholders. The aim of this study is to bring environmental consciousness in the soft TQM dimension of human resource management (HRM) and assess its interrelationship with stakeholder integration towards achieving a competitive advantage.

An empirical study was conducted in the transportation sector, specifically targeting managers in Greek shipping companies involved in global cargo transport and vessel operations. A structured questionnaire was administered, yielding 109 responses. The collected data were analyzed using partial least squares structural equation modeling.

The findings reveal the positive effect of both green HRM (GHRM) and stakeholder integration on the innovation differentiation advantage and market differentiation advantage of shipping companies. Results confirm the complementary (partial) mediating effect of GHRM in the relationship between stakeholder integration and both types of competitive advantage.

The primary limitation resides in data collection exclusively from shipping companies in Greece. A longitudinal approach would be beneficial for examining how the relationship between variables changes over time.

The findings of the study could assist shipping managers in their decisions to allocate resources for developing GHRM practices and for involving stakeholders in organizational practices to overcome competition.

This study contributes to the discourse on TQM by empirically investigating the combined impact of GHRM and stakeholder integration on competitive advantage – an aspect that has been relatively overlooked in existing literature.

Using a Problem Based Learning (PBL) approach, this paper examines whether internships can stand as a viable alternative to Higher Degree Apprenticeships (HDAs) within the UK Higher Education (HE) context. It was a process that was undertaken to identify work-integrated schemes as a part of a curriculum portfolio transformation project. This presented itself as a strategic avenue capable of fostering a competitive advantage (strategic differentiation), particularly in enhancing graduate employability through a differentiation in pedagogy employing Work-Integrated Learning (WIL).

This paper applied a PBL approach comprising of five distinct stages based on the McMaster Five-Point Strategy. This included the Problem Identification, Generating Solutions through a review of relevant literature and a case study, using an evaluation matrix to identify the best solution to Decide a Course of Action, Implementing the Solution and Evaluating the Solution. It presents an institutional and curriculum change project.

WIL can offer both strategic differentiation, an organisational distinctiveness within HE and Pedagogical differentiation, such as embedding internships in curriculum. This can be achieved by creating clear guidelines and expected outcome frameworks, bespoke feedback templates and enhanced collaboration, Experiential Learning pedagogy in the curriculum and the inclusion of other forms of WIL to further diversify and create a WIL organisational culture.

Practitioner use of applying problem-solving models for work-integrated curriculum planning.

We present a confluence of the concepts strategic differentiation and pedagogical differentiation using WIL as a conduit. We present this using a PBL evaluative review approach. The paper’s distinct contribution manifests in the formulation of three pivotal recommendations.

This study aims to deal with the case adaptation problem associated with continuous data by providing a non-zero base solution for knowledge users in solving a given situation.

Firstly, the neighbourhood transformation of the initial case base and the view similarity between the problem and the existing cases will be examined. Multiple cases with perspective similarity or above a predefined threshold will be used as the adaption cases. Secondly, on the decision rule set of the decision space, the deterministic decision model of the corresponding distance between the problem and the set of lower approximate objects under each choice class of the adaptation set is applied to extract the decision rule set of the case condition space. Finally, the solution elements of the problem will be reconstructed using the rule set and the values of the problem's conditional elements.

The findings suggest that the classic knowledge matching approach reveals the user with the most similar knowledge/cases but relatively low satisfaction. This also revealed a non-zero adaptation based on human–computer interaction, which has the difficulties of solid subjectivity and low adaptation efficiency.

In this study the multi-case inductive adaptation of the problem to be solved is carried out by analyzing and extracting the law of the effect of the centralized conditions on the decision-making of the adaptation. The adaption process is more rigorous with less subjective influence better reliability and higher application value. The approach described in this research can directly change the original data set which is more beneficial to enhancing problem-solving accuracy while broadening the application area of the adaptation mechanism.

The examination of the calculation cases confirms the innovation of this study in comparison to the traditional method of matching cases with tacit knowledge extrapolation.

The algorithm models established in this study develop theoretical directions for a multi-case induction adaptation study of tacit knowledge.

This study designs a multi-case induction adaptation scheme by combining NRS and CBR for implicitly knowledgeable exogenous cases. A game-theoretic combinatorial assignment method is applied to calculate the case view and the view similarity based on the threshold screening.

In this paper, we focus on how and when organizations adopt different types of ambidexterity to facilitate projects that operate with fundamentally different time scales compared with the dominant functions of the organization.

Using a comparative case study design, four case studies were conducted of long-term projects in two similar manufacturing plants within the same organization.

We found organizations first use structural and sequential ambidexterity in change efforts, during which new process knowledge is developed. When structural and sequential ambidexterity are not viable, change agents use this developed knowledge to support contextual ambidexterity. This contextual ambidexterity allows change agents to move between distinct time conceptions of event time and clock time.

One of the limitations of this study was that it only focused on two plants within one organization in order to control for variation. Future studies should look at a wider range of companies, technologies and industries.

While structurally and temporally decoupling change efforts help with differentiation of new technological change, there are limitations with these efforts. It is important to build an organization’s contextual ambidexterity as well as organizational supports to facilitate switching between clock time and event time.

This paper helps explain how and when organizations use different types of ambidexterity in resolving temporal conflicts when implementing longer-term technological change in fast-paced manufacturing settings.

This paper aims to discuss artifacts and how they influence the performative scheme of the routine and human agency. Artifacts emerge from a heterogeneous network of technical and social elements, which implies assuming that they strongly influence the performance of a routine and the organizing.

This essay starts from an established theoretical framework to develop reflections and propose that the artifacts entangle part of organizational knowledge and that the artifact's role is structured by their enactment in performing a routine, which gives them meaning and a sense of purpose.

The propositions contribute to theoretical and empirical advances by offering new insights for analysing the role of artifacts in routine dynamics. The main arguments presented are about (i) the existence of a potential role and a performed role for artifacts, (ii) that the artifacts' role evolves from knowledge and know-how embedded in routines and their actants and (iii) that artifacts are connected through networks of routines, and they embed a vast repertoire of knowledge and expertise.

Also, it proposes a fruitful research agenda based on the main reflections. Finally, the thoughts presented open a pandora's box to reflect on the intertwining between human and artifacts, not just in organizing but also in everyday social life.

This study aims to analyze the knowledge transfer process for implementing a company-specific production system (XPS) from a subsidiary of a multinational corporation (MNC) to its local suppliers.

A case study approach was adopted and applied in an automotive supply chain. Empirical data were collected from interviews, observations and internal documents.

The literature shows that the successful XPS implementation depends on the ability to transfer XPS knowledge; the motivation of the source unit to share XPS knowledge; the value and nature of knowledge embedded in XPS; the effectiveness of individual, social and organizational transfer mechanisms; the motivation and absorptive capacity of the target unit and, the organizational, social and relational contexts in which XPS is transferred. Based on the research findings, we develop 12 propositions and presented them in a framework.

This paper expands and enriches the literature on the knowledge transfer process of XPS. The proposed framework establishes theoretical propositions and associations raised by qualitative analysis. However, these propositions are potentially testable on a larger scale for broader generalization.

Managers can recognize critical factors and relationships needed to improve the XPS implementation from an MNC subsidiary to its local suppliers.

The proposed framework provides a scheme to capture the essential critical factors affecting a successful XPS implementation between MNC subsidiaries and local suppliers. Moreover, we found relevant associations between pairs of critical factors that were not identified in the literature.

Predicting student performance is crucial in educational settings to identify and support students who may need additional help or resources. Understanding and predicting student performance is essential for educators to provide targeted support and guidance to students. By analyzing various factors like attendance, study habits, grades, and participation, teachers can gain insights into each student’s academic progress. This information helps them tailor their teaching methods to meet the individual needs of students, ensuring a more personalized and effective learning experience. By identifying patterns and trends in student performance, educators can intervene early to address any challenges and help students acrhieve their full potential. However, the complexity of human behavior and learning patterns makes it difficult to accurately forecast how a student will perform. Additionally, the availability and quality of data can vary, impacting the accuracy of predictions. Despite these obstacles, continuous improvement in data collection methods and the development of more robust predictive models can help address these challenges and enhance the accuracy and effectiveness of student performance predictions. However, the scalability of the existing models to different educational settings and student populations can be a hurdle. Ensuring that the models are adaptable and effective across diverse environments is crucial for their widespread use and impact. To implement a student’s performance-based learning recommendation scheme for predicting the student’s capabilities and suggesting better materials like papers, books, videos, and hyperlinks according to their needs. It enhances the performance of higher education.

Thus, a predictive approach for student achievement is presented using deep learning. At the beginning, the data is accumulated from the standard database. Next, the collected data undergoes a stage where features are carefully selected using the Modified Red Deer Algorithm (MRDA). After that, the selected features are given to the Deep Ensemble Networks (DEnsNet), in which techniques such as Gated Recurrent Unit (GRU), Deep Conditional Random Field (DCRF), and Residual Long Short-Term Memory (Res-LSTM) are utilized for predicting the student performance. In this case, the parameters within the DEnsNet network are finely tuned by the MRDA algorithm. Finally, the results from the DEnsNet network are obtained using a superior method that delivers the final prediction outcome. Following that, the Adaptive Generative Adversarial Network (AGAN) is introduced for recommender systems, with these parameters optimally selected using the MRDA algorithm. Lastly, the method for predicting student performance is evaluated numerically and compared to traditional methods to demonstrate the effectiveness of the proposed approach.

The accuracy of the developed model is 7.66%, 9.91%, 5.3%, and 3.53% more than HHO-DEnsNet, ROA-DEnsNet, GTO-DEnsNet, and AOA-DEnsNet for dataset-1, and 7.18%, 7.54%, 5.43% and 3% enhanced than HHO-DEnsNet, ROA-DEnsNet, GTO-DEnsNet, and AOA-DEnsNet for dataset-2.

The developed model recommends the appropriate learning materials within a short period to improve student’s learning ability.

This study aims to demonstrate the evaluation of an incentive scheme to encourage pregnant people to set a quit-smoking date.

The paper outlines a collaborative approach, working with pregnant people, clinicians, tobacco dependency practitioners and academics to gain insights into their perspectives and experiences. Quantitative and qualitative data were analysed.

The incentive scheme and appropriate support from clinicians have been shown to encourage pregnant people to set a quit date. The tobacco dependency practitioners helped remove barriers, such as the perception of the stigmatisation of smoking when pregnant. The practitioners also helped pregnant people make informed decisions to support successful behaviour change. The impact of the scheme resulted in improved infant health indicators. The scheme’s evaluation also supported establishing stakeholder knowledge exchange and learning processes.

This is a single-site study among a relatively small group of people designed to achieve a specific evaluation objective. Caution in generalising to wider settings should be exercised.

This study highlights the efficacy of an incentive scheme, complemented with support from clinicians, and the significance of knowledge exchange and collaboration between stakeholders in health care with significance in similar settings.

The paper details the incentive scheme input, actions, output, outcomes and impact involving a wider range of stakeholders, including the emotional consequences for participants, clinicians and academics.