Search results

1 – 10 of over 261000
Content available
Article
Publication date: 19 July 2021

Johanna Gummerus, Jacob Mickelsson, Jakob Trischler, Tuomas Härkönen and Christian Grönroos

This paper aims to develop and apply a service design method that allows for stronger recognition and integration of human activities into the front-end stages of the…

Abstract

Purpose

This paper aims to develop and apply a service design method that allows for stronger recognition and integration of human activities into the front-end stages of the service design process.

Design/methodology/approach

Following a discussion of different service design perspectives and activity theory, the paper develops a method called activity-set mapping (ActS). ActS is applied to an exploratory service design project to demonstrate its use.

Findings

Three broad perspectives on service design are suggested: (1) the dyadic interaction, (2) the systemic interaction and (3) the customer activity perspectives. The ActS method draws on the latter perspective and focuses on the study of human activity sets. The application of ActS shows that the method can help identify and visualize sets of activities.

Research limitations/implications

The ActS method opens new avenues for service design by zooming in on the micro level and capturing the set of activities linked to a desired goal achievement. However, the method is limited to activities reported by research participants and may exclude unconscious activities. Further research is needed to validate and refine the method.

Practical implications

The ActS method will help service designers explore activities in which humans engage to achieve a desired goal/end state.

Originality/value

The concept of “human activity set” is new to service research and opens analytical opportunities for service design. The ActS method contributes a visualization tool for identifying activity sets and uncovering the benefits, sacrifices and frequency of activities.

Details

Journal of Service Management, vol. 32 no. 6
Type: Research Article
ISSN: 1757-5818

Keywords

To view the access options for this content please click here
Article
Publication date: 28 July 2021

Fatma Pakdil

Given the critical role of project prioritization and selection process in Six Sigma efforts, this study aims to analyse the relevant literature to answer this question…

Abstract

Purpose

Given the critical role of project prioritization and selection process in Six Sigma efforts, this study aims to analyse the relevant literature to answer this question: What types of project prioritization and selection methods have been used in Six Sigma research?

Design/methodology/approach

The study implemented the systematic literature review (SLR) method to identify and review all relevant previous studies.

Findings

The study revealed that 59 articles focused on the topic used 111 methods, analytic hierarchy process appeared as the most frequently used method with 12 articles (20%) and one-third of the methods used in the current Six Sigma project selection literature contained multi-criteria decision-making methods. In total, 61% of 59 articles were not published in the journals ranked by the ABDC’s list. Only 17% of the articles reviewed in this study were published in journals ranked as B category and 12% of the articles were published in A category journals.

Practical implications

The findings of this literature review may help Six Sigma practitioners and researchers accurately identify project prioritization and selection methods, considering that qualitative and quantitative scientific methods guarantee to make better decisions than “gut feelings” of the decision makers in this process.

Originality/value

Although a variety of studies focused on the topic, an SLR is lacking in the area of Six Sigma project prioritization and selection. Therefore, this study was constructed using the SLR method to analyse the topic.

Details

International Journal of Lean Six Sigma, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-4166

Keywords

To view the access options for this content please click here
Article
Publication date: 27 July 2021

William E. Donald

This paper offers a “content analysis of metadata, titles, and abstracts” (CAMTA) method underpinned by a newly evolved metadata, title, abstract, introduction…

Abstract

Purpose

This paper offers a “content analysis of metadata, titles, and abstracts” (CAMTA) method underpinned by a newly evolved metadata, title, abstract, introduction, methodology, results, analysis, and discussion (M-TAIMRAD) Framework.

Design/methodology/approach

Draws on innovations of content analysis from the field of health- care to offer a pragmatic and transparent method for conducting rigorous and valid research within the field of business and management.

Findings

Replicable and valid guidelines for conducting the CAMTA method are offered, including an illustration. This is followed by a critical examination of the potential applications and benefits of the method to the field of business and management research.

Originality/value

The CAMTA method enables researchers to assimilate and synthesise metadata, titles and abstracts as a means of identifying grounds for future research and theory development. This will help to advance the field and subsequently benefit the wider readership including fellow academics, practitioners and policymakers. The flexibility of the CAMTA method means that it can be used as a stand-alone method or combined as part of a mixed-methods approach.

Details

Management Research Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8269

Keywords

To view the access options for this content please click here
Article
Publication date: 19 July 2021

Hassan Abdolrezaei, Hassan Siahkali and Javad Olamaei

This paper aims to present a hybrid model to mid-term forecast the load of transmission substations based on the knowledge of expert site and multi-objective posterior…

Abstract

Purpose

This paper aims to present a hybrid model to mid-term forecast the load of transmission substations based on the knowledge of expert site and multi-objective posterior framework. The main important challenges in load forecasting are the different behavior of load in specific days. Regular days, holidays and special holidays, days after a holidays and days of load shifting are characterized by abnormal load profiles. The knowledge of these days is verified by expert operators in regional dispatching centers.

Design/methodology/approach

In this paper, a hybrid model for power prediction of transmission substations based on the combination of similar day selection and multi-objective posterior technique has been proposed. In the first step, the important data for prediction is provided. Posterior method is used in the second step for prediction that it is based on kernel functions. A multi-objective optimization has been formulated with three type of output accuracy measurement function that it is solved by non-dominated sorting genetic technique II (NSGT-II) method. TOPSIS way is used to find the best point of Pareto.

Findings

The presented method has been tested in four scenarios for three different transmission stations, and the test results have been compared. The presented results indicate that the presentation method has better results and is robust to different load characteristics, which can be used for better forecasting of different stations for better planning of repairs and network operation.

Originality/value

The main contributions of this paper can be categorized as follows: A hybrid model based on similar days selection and multi-objective framework posterior is presented. Similar day selection is done by expert site that the day type and days with scheduled repair are considered. Hyperparameters of posterior process are found by NSGT-II based on TOPSIS method.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

To view the access options for this content please click here
Article
Publication date: 27 July 2021

Manpreet Kaur, Sanjeev Kumar and Munish Kansal

The purpose of the article is to construct a new class of higher-order iterative techniques for solving scalar nonlinear problems.

Abstract

Purpose

The purpose of the article is to construct a new class of higher-order iterative techniques for solving scalar nonlinear problems.

Design/methodology/approach

The scheme is generalized by using the power-mean notion. By applying Neville's interpolating technique, the methods are formulated into the derivative-free approaches. Further, to enhance the computational efficiency, the developed iterative methods have been extended to the methods with memory, with the aid of the self-accelerating parameter.

Findings

It is found that the presented family is optimal in terms of Kung and Traub conjecture as it evaluates only five functions in each iteration and attains convergence order sixteen. The proposed family is examined on some practical problems by modeling into nonlinear equations, such as chemical equilibrium problems, beam positioning problems, eigenvalue problems and fractional conversion in a chemical reactor. The obtained results confirm that the developed scheme works more adequately as compared to the existing methods from the literature. Furthermore, the basins of attraction of the different methods have been included to check the convergence in the complex plane.

Originality/value

The presented experiments show that the developed schemes are of great benefit to implement on real-life problems.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Book part
Publication date: 16 August 2011

Avinash Arya

This note presents a method of teaching accounting problems involving the use of the effective interest method such as bonds, notes, capital leases, and installment sales…

Abstract

This note presents a method of teaching accounting problems involving the use of the effective interest method such as bonds, notes, capital leases, and installment sales. The method is conceptually sound and simpler than the traditional method found in current textbooks and stimulates student interest by focusing on the economics of the transaction and relating it to real-life examples.

To assess its pedagogical efficacy, the method was tested in the introductory and intermediate accounting classes. In both courses, the results indicate that students' test scores are significantly higher under the new method than the traditional method. It is hoped that this evidence of the superiority of the new method in a classroom environment will spur its adoption by instructors and textbook writers.

Details

Advances in Accounting Education: Teaching and Curriculum Innovations
Type: Book
ISBN: 978-1-78052-223-4

To view the access options for this content please click here
Article
Publication date: 17 June 2021

Ankush Balaram Pawar, Dr. Shashikant U. Ghumbre and Dr. Rashmi M. Jogdand

Cloud computing plays a significant role in the initialization of secure communication between users. The advanced technology directs to offer several services, such as…

Abstract

Purpose

Cloud computing plays a significant role in the initialization of secure communication between users. The advanced technology directs to offer several services, such as platform, resources, and accessing the network. Furthermore, cloud computing is a broader technology of communication convergence. In cloud computing architecture, data security and authentication are the main significant concerns.

Design/methodology/approach

The purpose of this study is to design and develop authentication and data security model in cloud computing. This method includes six various units, such as cloud server, data owner, cloud user, inspection authority, attribute authority, and central certified authority. The developed privacy preservation method includes several stages, namely setup phase, key generation phase, authentication phase and data sharing phase. Initially, the setup phase is performed through the owner, where the input is security attributes, whereas the system master key and the public parameter are produced in the key generation stage. After that, the authentication process is performed to identify the security controls of the information system. Finally, the data is decrypted in the data sharing phase for sharing data and for achieving data privacy for confidential data. Additionally, dynamic splicing is utilized, and the security functions, such as hashing, Elliptic Curve Cryptography (ECC), Data Encryption Standard-3 (3DES), interpolation, polynomial kernel, and XOR are employed for providing security to sensitive data.

Findings

The effectiveness of the developed privacy preservation method is estimated based on other approaches and displayed efficient outcomes with better privacy factor and detection rate of 0.83 and 0.65, and time is highly reduced by 2815ms using the Cleveland dataset.

Originality/value

This paper presents the privacy preservation technique for initiating authenticated encrypted access in clouds, which is designed for mutual authentication of requester and data owner in the system.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

To view the access options for this content please click here
Article
Publication date: 9 July 2021

Mohsen Sadeghi Dastaki, Abbas Afrazeh and Masoud Mahootchi

Over the past years, many studies have explored the role of knowledge management (KM) in companies. KM is concerned with the measurement of knowledge to manage knowledge…

Abstract

Purpose

Over the past years, many studies have explored the role of knowledge management (KM) in companies. KM is concerned with the measurement of knowledge to manage knowledge efficiently. On the other hand, the intangible nature of knowledge makes its measurement challenging. Furthermore, there is no standardized method to measure knowledge, and it is chiefly measured based on the subjective judgment of researchers. Moreover, New Product Development (NPD) departments in many companies strive to assess their knowledge in terms of company products and knowledge workers. Hence, this study aims to propose a product-based two-phase technique that measures the company knowledge inventory.

Design/methodology/approach

In the first phase, the value of knowledge is quantified relative to products, knowledge workers and the entire company using two concepts of knowledge width and depth. Then, a three-dimensional knowledge asset map (knowledge, products and knowledge worker dimensions) is designed to assess and audit knowledge workers. Finally, this technique recruits an integer linear programming model with a cost minimization objective function to optimize the supply of NPD knowledge requirements in the second phase.

Findings

This model enables managers to determine what type of knowledge can be supplied by existing knowledge workers, whether within the company or by other external sources.

Originality/value

Among existing knowledge measurement methods, only a few use a product-based measuring technique. However, they fail to offer suitable scenarios for managers' decision-making process and consider cost structures in measurement techniques. Hence, this paper attempts to overcome these drawbacks.

Details

Journal of Knowledge Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1367-3270

Keywords

Content available
Article
Publication date: 24 June 2021

Bo Wang, Guanwei Wang, Youwei Wang, Zhengzheng Lou, Shizhe Hu and Yangdong Ye

Vehicle fault diagnosis is a key factor in ensuring the safe and efficient operation of the railway system. Due to the numerous vehicle categories and different fault…

Abstract

Purpose

Vehicle fault diagnosis is a key factor in ensuring the safe and efficient operation of the railway system. Due to the numerous vehicle categories and different fault mechanisms, there is an unbalanced fault category problem. Most of the current methods to solve this problem have complex algorithm structures, low efficiency and require prior knowledge. This study aims to propose a new method which has a simple structure and does not require any prior knowledge to achieve a fast diagnosis of unbalanced vehicle faults.

Design/methodology/approach

This study proposes a novel K-means with feature learning based on the feature learning K-means-improved cluster-centers selection (FKM-ICS) method, which includes the ICS and the FKM. Specifically, this study defines cluster centers approximation to select the initialized cluster centers in the ICS. This study uses improved term frequency-inverse document frequency to measure and adjust the feature word weights in each cluster, retaining the top τ feature words with the highest weight in each cluster and perform the clustering process again in the FKM. With the FKM-ICS method, clustering performance for unbalanced vehicle fault diagnosis can be significantly enhanced.

Findings

This study finds that the FKM-ICS can achieve a fast diagnosis of vehicle faults on the vehicle fault text (VFT) data set from a railway station in the 2017 (VFT) data set. The experimental results on VFT indicate the proposed method in this paper, outperforms several state-of-the-art methods.

Originality/value

This is the first effort to address the vehicle fault diagnostic problem and the proposed method performs effectively and efficiently. The ICS enables the FKM-ICS method to exclude the effect of outliers, solves the disadvantages of the fault text data contained a certain amount of noisy data, which effectively enhanced the method stability. The FKM enhances the distribution of feature words that discriminate between different fault categories and reduces the number of feature words to make the FKM-ICS method faster and better cluster for unbalanced vehicle fault diagnostic.

Details

Smart and Resilient Transport, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2632-0487

Keywords

To view the access options for this content please click here
Article
Publication date: 9 July 2021

Peng Li, Ju Liu, Cuiping Wei and Jian Liu

China is a critical factor for constructing an all-round well-off society. Infrastructure construction, especially high-grade highways, in the western area is an essential…

Abstract

Purpose

China is a critical factor for constructing an all-round well-off society. Infrastructure construction, especially high-grade highways, in the western area is an essential component of the strategy for large-scale development of west China. It is crucial to evaluate investment projects for high-grade highways and select the best one. Testing investment projects and selecting the best one can be recognized as a multicriteria decision-making (MCDM) problem. In this process, decision-makers (DMs) usually face with uncertain information because of complicated decision environment or their limited knowledge.

Design/methodology/approach

A new Evaluation based on the Distance from Average Solution (EDAS) for PFS based on the DEMATEL is proposed: The authors offer a new score function and prove some properties for the score function. They put forward a novel Decision-making Trial and Evaluation Laboratory (DEMATEL) method for PFS to analyze the relations of criteria and get criteria weights. Considering the bounded rationality of DM, the authors propose a new EDAS method for PFS based on prospect theory. They apply their proposed approach to a western city's actual case in selecting a suitable project for building a high-grade highway.

Findings

By comparison, the authors can observe that our method has some traits: (1) considering bounded rationality of DM; (2) fewer computation; (3) having the ability to obtain the relation of criteria and finding the critical factor in the decision system.

Originality/value

In this paper, the authors propose a new EDAS method for PFS based on the DEMATEL technique. They transform PFS into crisp numbers by their proposed new score function for PFN to make the decision process more convenient. Then, the authors use the DEMATEL method to obtain the relationship between criteria and criteria weights. Furthermore, they propose a new EDAS method for PFS based on DEMATEL to reduce the computational complexity. Finally, they apply our method to a real case and compare our method with two traditional methods.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

1 – 10 of over 261000