Search results

Lean enterprise (LE) is one of the emerging fields because of its impact across industry sectors. There were many LE framework articles published in the past without reviewing or considering the already published literature which lead to lots of inconsistencies in the existing frameworks of LE. This study aims to critically review the existing frameworks to identify inconsistencies and propose a new LE framework to overcome limitations of the existing LE frameworks.

A systematic literature review was conducted to identify the existing LE frameworks. All these identified frameworks were classified based on the following criteria: novelty of the framework; based on participation of academicians/practitioners/consultants; whether the proposed frameworks were verified; type of verification methodology used; and the degree of standardization of LE elements. A comprehensive LE framework was proposed after a thorough review of the existing LE frameworks which has been validated through reliability analysis and validity analysis.

The analysis revealed major inconsistencies such as lack of adaptation of existing frameworks in literature which lead to incoherent elements in LE frameworks. The study also found shortage of significant participation of academicians and practitioners in LE frameworks development compared to consultants. The present work established a road map to find a “cohesive theory of LE”, which resulted in the development of a set of coherent elements. Finally, a comprehensive LE framework was proposed with the help of extensive literature review. The initially proposed 106 elements were condensed to 50 after the validation to increase the focus and relevance.

The proposed LE framework needs to be validated via an empirical approach or clinical approach such as a case study which will be the future work.

The present study performed extensive literature review to identify LE-related articles, corresponding elements and established coherency among them. A new comprehensive framework was proposed.

The purpose of this paper is to verify the applicability of proposed lean production system (LPS) framework in the Indian manufacturing industry.

The authors conducted a cross-sectional study to collect responses from five major sectors, namely, automobile, process, machines and equipment, electronics and components and textile. They collected 200 responses to perform empirical validation from Indian manufacturing industry. They performed reliability analysis on the proposed framework of LPS in the Indian manufacturing industry.

The findings revealed that all the elements and sub-elements have a high value in reliability. Subsequently, the study performed principles component analysis on LPS framework. The empirical investigation revealed that the proposed LPS framework has a high level of reliability as well as validity in the Indian manufacturing industry. Hence, the study concluded that the LPS framework is helpful to implement lean principles in a structured manner in any Indian manufacturing industry to achieve excellence in organizational functions.

The authors conducted an empirical survey to verify the applicability of the proposed LPS framework in the Indian manufacturing industry. They observed that many researchers proposed various LPS frameworks, but none of the researchers focused on verifying the proposed frameworks. To overcome, the same limitations, the study verified the proposed framework with the larger sample size.

Existing conceptual, empirical and case studies evidence suggests that manufacturing industries find the joint implementation of Kaizen philosophy initiatives. However, the existing practices rarely demonstrated in a single framework and implementation procedure in a structure nature. This paper, therefore, aims to develop, validate and practically test a framework and implementation procedure for the implementation of integrated Kaizen in manufacturing industries to attain long-term improvement of operational, innovation, business (financial and marketing) processes, performance and competitiveness.

The study primarily described the problem, extensively reviewed the current state-of-the-art literature and then identified a gap. Based on it, generic and comprehensive integrated framework and implementation procedure is developed. Besides, the study used managers, consultants and academics from various fields to validate a framework and implementation procedure for addressing business concerns. In this case, the primary data was collected through self-administered questionnaire, and 244 valid questionnaires were received and were analyzed. Furthermore, the research verified the practicability of the framework by empirically exploring the current scenario of selected manufacturing companies.

The research discovered innovative framework and six-phase implementation procedure to fill the existing conceptual gap. Furthermore, the survey-based and exploratory empirical analysis of the research demonstrated that the practice of the proposed framework based on structured procedure is valued and companies attain the middling improvements of productivity, delivery time, quality, 5S practice, waste and accident rate by 61.03, 44, 52.53, 95.19, 80.12, and 70.55% respectively. Additionally, the companies saved a total of 14933446 ETH Birr and 5,658 M² free spaces. Even though, the practices and improvements vary from company to company, and even companies unable to practice some of the unique techniques of the identified CI initiatives considered in the proposed framework.

All data collected in the survey came from professionals working for Ethiopian manufacturing companies, universities and government. It is important to highlight that n = 244 is high sample size, which is adequate for a preliminary survey but reinforcing still needs further survey in terms of generalization of the results since there are hundreds of manufacturing companies, consultants and academicians implementing and consulting Kaizen. Therefore, a further study on a wider Ethiopian manufacturing companies, consultants and academic scale would be informative.

This work is very important for Kaizen professionals in the manufacturing industry, academic and government but in particular for senior management and leadership teams. Aside from the main findings on framework development, there is some strong evidence that practice of Kaizen resulted in achieving quantitative (monetary and non-monetary) and qualitative results. Thus, senior management teams should use this research out to practice and analyze the effect of Kaizen on their own organizations. Within the academic community, this study is one of the first focusing on development, validating and practically testing and should aid further study, research and understanding of Kaizen in manufacturing industries.

So far, it is rare to find preceding studies proposed, validated and practically test an integrated Kaizen framework with the context of manufacturing industries. Thus, authors understand that this is the very first research focused on the development of the framework for manufacturing industries continuously to be competitive and could help managers, institutions, practitioners and academicians in Kaizen practice.

Change literature emphasizes the significance of aligning change at a systemic level for sustained effectiveness of strategic change initiatives. While this body of literature emphasizes the significance of psychological and process dimensions of managing change, research on an integrated and strategic approach to deploy, track, measure and sustain large‐scale changes has been limited and inconclusive. The purpose of this paper is to address this gap in the literature to propose a holistic conceptual framework for identifying, formulating, deploying, measuring, aligning and tracking strategic changes in organizations.

Specifically, core concepts drawn from scholarly literature and practitioner writings from distinct fields of change management and strategy deployment tools, primarily the Balanced Scorecard (BSC) as proposed by Kaplan and Norton, are reviewed, synthesized and critiqued, to inform and advance the integrated framework proposed.

The suggested approach draws significantly from the BSC framework and focuses on the use of formal steps such as developing change themes and results, setting change objectives, developing lead and lag performance measures for measuring strategic change objectives. Furthermore, the proposed framework also provides directions on how to track the progress of change initiatives with respect to the desired objectives, for evaluating the effectiveness of change deployment efforts, all through applying cause and effect linkages.

Although the focus on individual change arose to support technical deployment of change, over the years the strategic deployment process itself has not received the desired focus in the change strategy literature. The proposed framework extends the current literature on strategic change to offer academics fresh insights on the significance of a strategic approach to change deployment. An application of the framework in the context of large‐scale transformational changes in organizations can provide further evidence related to the validity of the proposed approach.

A total of 70 percent of all change efforts fail. While some fail due to incomplete diagnoses, others fail due to gaps in deployment or measurement. However, there is uncertainty about how to prevent change failure, with no one having explicitly articulated the same. A rigorous and practical approach to systematically deploy change with a continuous focus on strategic alignment has specifically been found missing in the literature. The proposed framework fills this gap to offer managers and organizational decision makers a holistic and practical tool to successfully navigate the complexities of their strategic change efforts by measuring strategic alignment in a step‐wise manner throughout the change process.

Mention of the need to use integrated and strategic performance management tools, such as the BSC proposed by Kaplan and Norton, to measure and review change and to manage the change process has been found in recent literature. However, no studies have yet provided any direction on “how” to use such integrated and strategic tools throughout the change process, to deploy measure and ensure continuous strategic alignment during transformational changes. The paper addresses this gap to propose a systematic, integrated and holistic approach for aligning change deployment.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

The purpose of this paper is to investigate and propose a framework for environmental impact assessment of packaging material being used to package a product.

The research considers parameters identified in the literature by the use of “Delphi Technique”. Based on available data, methods of measurement of the parameters are carried out. Furthermore, a metrics is proposed for measurement of environmental impact. Based on the metrics, the research proposes a framework for environmental impact assessment by use of Dominic’s method. The research validates the proposed framework through Pahl and Beitz method.

The proposed framework establishes a metrics for measurement of 16 parameters for environmental impact assessment. The framework can be used to compare a set of alternate packaging material for the same product for its environmental impact. The framework also provides a quantitative measure of the environmental impact assessment of a product packaging.

The research can be used to evaluate a packaging as compared to its alternate. It can also be used to propose suggestions for improving the environmental impact of packaging in comparison to its alternate.

The data considered for establishing of metrics for measurement of parameters for environmental impact may not be available in all practical situations in the similar way as considered in the research.

This paper proposes a framework for environmental impact assessment for product packaging considering data in the Indian scenario.

The purpose of this study is to verify that if applications categories are segmented and resources are allocated based on their specific category, how effective scheduling can be done?.

This paper proposes a scheduling framework for IoT application jobs, based upon the Quality of Service (QoS) parameters, which works at coarse grained level to select a fog environment and at fine grained level to select a fog node. Fog environment is chosen considering availability, physical distance, latency and throughput. At fine grained (node selection) level, a probability triad (C, M, G) is anticipated using Naïve Bayes algorithm which provides probability of newly submitted application job to fall in either of the categories Compute (C) intensive, Memory (M) intensive and GPU (G) intensive.

Experiment results showed that the proposed framework performed better than traditional cloud and fog computing paradigms.

The proposed framework combines types of applications and computation capabilities of Fog computing environment, which is not carried out to the best of knowledge of authors.

This paper aims to present an alternative practical framework to classify the skill and knowledge of the individual trainees by comparing it with the expert in an organization. This framework gives the benefit to the organization in order to know the ability level of the personnel and to be able to provide the personnel development method both in academic learning and workplace learning.

This research develops the framework based on relevant methodologies. Competency-Based Development is applied to investigate the knowledge and skill of the specific task. Knowledge Engineering is used to capture the experiences and construct knowledge model from relevance parties. Capability Maturity Model is then adapted to develop the capability and maturity level of the personnel. It can then be used to cluster the knowledge and skill. Finally, the Substation Maintenance Department of Provincial Electricity Authority (PEA), Thailand, is selected as a case study to test the proposed framework.

The results have shown that the proposed framework can be utilized to identify the capability level of the individual personnel. Furthermore, the appropriate maturity development of the employees in each level can also be identified. This proposed framework provides better results when comparing to the current PEA competency model, as the criteria in this framework are systematically derived from experts rather than relying solely on the proficiency level. Although, this framework was tested with the switchgear maintenance task, the results and its systematic approach have indicated that it can also be used to develop the capability maturity model for other fields of work.

The main originality of this research is the proposed competency analysis table, which integrates human resource development with knowledge management, risks management and management information system. Rather than performing these tasks separately for continuous quality improvement, organization can practically plan and perform the quality improvement-related tasks spontaneously. Moreover, the application of the capability maturity model to classify knowledge and skill of the maintenance tasks into maturity level is another academic value presented in this paper. The proposed framework gives the benefit to organization to classify the capability of the personnel. This is potentially beneficial to the human resource development personnel than traditional methods in the sense that it provides the information on how to develop the specific skill of the employees.

The concept of “green product development (GPD)” has been emerged as a global phenomenon. The main objective of GPD is to minimize the impact of industrial growth on the environment across the globe. Many researchers have actively contributed articles for developing GPD, but none of them provide direction and guidance for an effective implementation of GPD in organizations. Thus, the purpose of this paper is to identify a comprehensive list of the principles, practices, tools and techniques, and integrate them to develop and propose a new framework for GPD for effective implementation in organizations.

The present study has examined 37 frameworks published from 1991 to 2012 in selected 23 peer reviewed journals. The study has also identified pillars of the framework with the help of comparative analysis performed on the selected GPD frameworks. The study has formed a team to identify critical elements in the field of GPD. The team consisted academicians, practitioner and consultant.

The findings of the present paper bring out extremely incoherent utilization of elements for implementing GPD. The study has identified 80 unique elements and 11 pillars to propose a comprehensive conceptual framework in the field of GPD with the help of comparative analysis. Also, the present study analysis of selected research articles founds that future research in GPD should be directed towards finding a coherent set of elements that may be further employed to formulate and execution of frameworks. To achieve the required task, the study has proposed a conceptual comprehensive framework in the field of GPD with the help of extensive literature survey and comparative analysis.

The study has conducted extensive literature survey using various online portals and sources. It has not only performed critical review on existing sample of the frameworks but also raised the issue of what is really a framework and how to identify the frameworks from the literature. The study also provides guidelines to the future researchers to propose new frameworks in the field of GPD.

Failure in engaging shop floor employees (including supervisory staff) in lean, lacking of supervisory skills in leading workers and lacking of lean technical knowhow among the shop floor employees are some of the major obstacles in lean transformation. One of the reasons of inefficient lean transformation is the shortages in frameworks or plans in implementing lean. The purpose of this paper is to investigate the shortfalls in the current lean implementation frameworks.

The frameworks were analysed according to the following criteria: first, “What” is the approach of lean implementation, i.e. top-down or bottom-up; second, “How” to implement lean (description of steps or sequences of lean implementation along the lean journey); third, “Why” – the reason of adoption of the proposed lean tools, techniques or practices (thereafter TTPs) in each phase of lean implementation; and fourth, “Who” are the targeted internal stakeholders to use or apply the lean TTPs that were proposed in the frameworks.

Most of the current available lean frameworks were prone to top-down approach but not bottom-up. Improvement initiatives from the shop floor employees were often overlooked by researchers. In proposing their frameworks, most of the researchers have neglected the importance of “Why” aspect in the adoption of TTPs or the framework itself without giving the “reason” for each of the elements in lean implementation. Besides the aspects of “What” and “How”, the mentioned “Why” aspect is important in contributing to capability building among the shop floor employees in carrying out improvement, problem-solving or waste elimination activities. The aspect of “Who should carry out which lean TTP” was somewhat not emphasised by most of the lean researchers. In addition, the current frameworks were prone to “one-best-way” approach with lacking of contingency sense, which is one of the common criticisms against Lean Production System.

This paper provides a critical view on the shortfalls of current lean implementation frameworks, and proposes an insight of new criteria for future research in analysing and proposing new lean implementation framework towards lean transformation.