Ahmad Jafarnejad, Mansoor Momeni, Seyed Hossein Razavi Hajiagha and Maryam Faridi Khorshidi
Medical equipment’s supply chains play a vital role in performance of national 1healthcare systems. This supply chain is confronted with different internal and external risks. The…
Abstract
Purpose
Medical equipment’s supply chains play a vital role in performance of national 1healthcare systems. This supply chain is confronted with different internal and external risks. The purpose of this study is to investigate and find the key factors affecting the resilience of the supply chain of medical equipment and to examine the dynamic relations among these factors.
Design/methodology/approach
A hybrid methodology is used for meeting the purpose of this study. First, the Delphi method is extended by using hesitant fuzzy linguistic term sets to identify the key factors of supply chain resilience. At the second phase, using the system dynamic methodology, the dynamic relations among identified resilience factors are analyzed.
Findings
Using the Delphi method, agility, collaboration among actors, sharing of information, trust among actors, explicitness of supply chain, risk management culture, adaptability, structure, funding and environment conditions are identified as ten major factors affecting medical equipment’s supply chain resilience. Also, four scenarios are simulated along with their impacts on the system.
Originality/value
The main contribution of this study is extending a hesitant fuzzy linguistic term sets-based Delphi and applying it along a system dynamic analysis to identify the key factors affecting resilience of medical equipment’s supply chain for the first time.
Details
Keywords
Mohamadreza Mahmoudi, Hannan Amoozad Mahdiraji, Ahmad Jafarnejad and Hossein Safari
The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main…
Abstract
Purpose
The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW).
Design/methodology/approach
To realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated.
Findings
To prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.
Originality/value
In this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu.
Details
Keywords
Bayu Giri Prakosa, Danur Condro Guritno, Theresia Anindita, Mahrus Kurniawan and Ahmad Cahyo Nugroho
This study aims to analyze how ready a firm is to transform into Industry 4.0 using the Readiness Index (INDI 4.0) assessment. It also investigates the differences (before and…
Abstract
Purpose
This study aims to analyze how ready a firm is to transform into Industry 4.0 using the Readiness Index (INDI 4.0) assessment. It also investigates the differences (before and after) of the program “Making Indonesia 4.0” in 2018 in socioeconomic and demographic aspects.
Design/methodology/approach
The INDI 4.0 assessment involved a self-evaluation by 622 companies across 13 industry sectors, subsequently verified by the Ministry of Industry. This study incorporates discussions with industry experts to enhance the interpretation of the analytical findings.
Findings
This study explores the interrelation among the components of INDI 4.0 across different levels, assessing the readiness of each sector for Industry 4.0. The findings reveal the diverse impact of implementing Industry 4.0 in Indonesia on socioeconomic and demographic aspects. Furthermore, the study proposes several policy recommendations for the Indonesian government’s consideration.
Research limitations/implications
This study’s scope is confined to the industrial context of Indonesia, as the assessment components are tailored to the specific characteristics and culture of the country’s industry. Subsequent research endeavors can leverage this study as a foundational reference, adapting the components to align with the particular interests of other nations.
Practical implications
Businesses, especially those in Indonesia, can employ these findings to evaluate their position in the context of Industry 4.0 transformation compared to their industry. Simultaneously, the Indonesian government can use these results as a starting point to evaluate and potentially enhance their policies related to Industry 4.0. We recommend five policy proposals for the Indonesian government: diversifying measurement models, shifting terminology, emphasizing soft skills, promoting continuous learning and implementing Center of Digital Industry Indonesia 4.0 (PIDI 4.0) initiatives.
Social implications
This study offers a broad impact of Industry 4.0 implementation in socioeconomic and demographic aspects in Indonesia, such as income, job-shifting, age, educational background and gender.
Originality/value
To the best of our knowledge, no prior research has explored the repercussions of industrial implementation on socioeconomic and demographic facets.
Details
Keywords
Sameh M Saad, Ramin Bahadori and Hamidreza Jafarnejad
This study proposes the Smart SME Technology Readiness Assessment (SSTRA) methodology which aims to enable practitioners to assess the SMEs Industry 4.0 technology readiness…
Abstract
Purpose
This study proposes the Smart SME Technology Readiness Assessment (SSTRA) methodology which aims to enable practitioners to assess the SMEs Industry 4.0 technology readiness throughout the end-to-end engineering across the entire value chain; the smart product design phase is the focus in this paper.
Design/methodology/approach
The proposed SSTRA utilises the analytic hierarchy process to prioritise smart SME requirements, a graphical interface which tracks technologies' benchmarks under Industry 4.0 Technology Readiness Levels (TRLs); a mathematical model used to determine the technology readiness and visual representation to understand the relative readiness of each smart main area. The validity of the SSTRA is confirmed by testing it in a real industrial environment. In addition, the conceptual model for Smart product design development is proposed and validated.
Findings
The proposed SSTRA offers decision-makers the facility to identify requirements and rank them to reflect the current priorities of the enterprise. It allows SMEs to assess their current capabilities in a range of technologies of high relevance to the Industry 4.0 area. The SSTRA assembles a readiness profile allowing decision-makers to not only perceive the overall score of technology readiness but also the distribution of technology readiness across the main smart areas. It helps to visualise strengths and weaknesses; whilst emphasising the fundamental gaps that require serious action to assist the program with a well-balanced effort towards a successful transition to Industry 4.0.
Originality/value
The SSTRA provides a step-by-step approach for decision-making based on data collection, analysis, visualisation and documentation. Hence, it greatly mitigates the risk of further Industry 4.0 technology investment and implementation.
Details
Keywords
Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable…
Abstract
Purpose
Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.
Design/methodology/approach
An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.
Findings
On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.
Originality/value
The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.
Details
Keywords
Saira Tanweer, Tariq Mehmood, Saadia Zainab, Zulfiqar Ahmad, Muhammad Ammar Khan, Aamir Shehzad, Adnan Khaliq, Farhan Jahangir Chughtai and Atif Liaqat
Innovative health-promoting approaches of the era have verified phytoceutics as one of the prime therapeutic tools to alleviate numerous health-related ailments. The purpose of…
Abstract
Purpose
Innovative health-promoting approaches of the era have verified phytoceutics as one of the prime therapeutic tools to alleviate numerous health-related ailments. The purpose of this paper is to probe the nutraceutic potential of ginger flowers and leaves against hyperglycemia.
Design/methodology/approach
The aqueous extracts of ginger flowers and leaves were observed on Sprague Dawley rats for 8 weeks. Two parallel studies were carried out based on dietary regimes: control and hyperglycemic diets. At the end of the experimental modus, the overnight fed rats were killed to determine the concentration of glucose and insulin in serum. The insulin resistance and insulin secretions were also calculated by formulae by considering fasting glucose and fasting insulin concentrations. Furthermore, the feed and drink intakes, body weight gain and hematological analysis were also carried out.
Findings
In streptozotocin-induced hyperglycemic rats, the ginger flowers extract depicted 5.62% reduction; however, ginger leaves extract reduced the glucose concentration up to 7.11% (p = 0.001). Similarly, ginger flowers extract uplifted the insulin concentration up to 3.07%, while, by ginger leaves extract, the insulin value increased to 4.11% (p = 0.002). For the insulin resistance, the ginger flower showed 5.32% decrease; however, the insulin resistance was reduced to 6.48% by ginger leaves (p = 0.014). Moreover, the insulin secretion increased to 18.9% by flower extract and 21.8% by ginger leave extract (p = 0.001). The feed intake and body weight gain increased momentously by the addition of ginger flowers and leaves; however, the drink intake and hematological analysis remained non-significant by the addition of ginger parts.
Originality/value
Conclusively, it was revealed that leaves have more hypoglycemic potential as compared to flowers.
Details
Keywords
Muhammad Shakeel Aslam and Ayesha Akram
This study aims investigate the effects of electronic human resource management (e-HRM) on communication pace and processing time reduction through the mediation of organizational…
Abstract
Purpose
This study aims investigate the effects of electronic human resource management (e-HRM) on communication pace and processing time reduction through the mediation of organizational agility. The study also investigates the moderating role of technological attitude (TA) on the relationship between e-HRM and organizational agility.
Design/methodology/approach
The data was collected from 331 information and communication technology (ICT) companies – one respondent from each company working in the Human Resource Management (HRM) department. The data was analyzed through the partial least square structural equational model (PLS-SEM) using WarpPLS7.0 software to test the study’s hypotheses.
Findings
We found that e-HRM has positive significant effects on communication pace and processing time reduction through the mediation of organizational agility. Furthermore, TA is found to be positively moderating the relationship between e-HRM and organizational agility.
Research limitations/implications
The study adds significant value to the existing knowledge base on e-HRM by providing empirical insights about the role of e-HRM in optimizing the communication pace and processing time of today’s businesses.
Practical implications
The study also provides invaluable insights to practitioners to replace conventional HR systems with e-HRM to better perform HR functions by optimizing communication pace and processing time in the current fast-paced era.
Originality/value
E-HRM has become an issue of great significance in the contemporary corporate landscape to improve operational efficiency. Despite its widespread adoption in the corporate world, empirical evidence on e-HRM, particularly on its consequences, is still inconclusive.
Details
Keywords
Madjid Tavana, Akram Shaabani and Naser Valaei
Delivering premium services and quality products are critical strategies for success in manufacturing. Continuous improvement (CI), as an underlying foundation for quality…
Abstract
Purpose
Delivering premium services and quality products are critical strategies for success in manufacturing. Continuous improvement (CI), as an underlying foundation for quality management, is an ongoing effort allowing manufacturing companies to see beyond the present to create a bright future. We propose a novel integrated fuzzy framework for analyzing the barriers to the implementation of CI in manufacturing companies.
Design/methodology/approach
We use the fuzzy failure mode and effect analysis (FMEA) and a fuzzy Shannon's entropy to identify and weigh the most significant barriers. We then use fuzzy multi-objective optimization based on ratio analysis (MOORA), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy simple additive weighting (SAW) methods for prioritizing and ranking the barriers with each method. Finally, we aggregate these results with Copeland's method and extract the main CI implementation barriers in manufacturing.
Findings
We show “low cooperation and integration of the team in CI activities” is the most important barrier in CI implementation. Other important barriers are “limited management support in CI activities,” “low employee involvement in CI activities,” “weak communication system in the organization,” and “lack of knowledge in the organization to implement CI projects.”
Originality/value
We initially identify the barriers to the implementation of CI through rigorous literature review and then apply a unique integrated fuzzy approach to identify the most important barriers based on the opinions of industry experts and academics.
Details
Keywords
Sami Ullah, Mohit Kukreti, Abdul Sami and Muhammad Rehan Shaukat
This research explains the critical role of technological readiness and green dynamic capabilities in enhancing the sustainability performance of manufacturing firms, which is…
Abstract
Purpose
This research explains the critical role of technological readiness and green dynamic capabilities in enhancing the sustainability performance of manufacturing firms, which is pivotal for achieving the United Nations’ Sustainable Development Goals. The theoretical framework is grounded in the dynamic capability theory, positing that technological readiness enhances a firm’s green dynamic capabilities, and employee green behavior moderates the effect on the sustainability performance of manufacturing firms.
Design/methodology/approach
Quantitative data from 1,660 managerial employees of a diverse sample of manufacturing firms was aggregated at the firm level using interclass correlation and interrater agreement, ensuring robustness using at least two responses per firm. With the final dataset of 418 firms, structural equation modeling was conducted using AMOS26.
Findings
The findings reveal that technological readiness positively affects sustainability performance and enhances it through green dynamic capabilities. Furthermore, the study highlights the positive moderating role of employees’ green behavior, amplifying the impact of green dynamic capabilities on sustainability performance.
Originality/value
This research makes a novel contribution to the body of knowledge by integrating dynamic capability theory with empirical evidence on sustainability performance. It represents a significant step toward promoting a more sustainable and responsible future for organizations and society and provides comprehensive insights into the complex interplay of these variables. These insights are crucial for academia, industry practitioners and policymakers striving to foster sustainable practices within the manufacturing sector.
Details
Keywords
The purpose of this paper is to present the design and implementation of a genetic algorithm (GA), using a large language model (LLM) for optimizing the delivery scheduling…
Abstract
Purpose
The purpose of this paper is to present the design and implementation of a genetic algorithm (GA), using a large language model (LLM) for optimizing the delivery scheduling process in warehouses of third-party logistics (3PL) companies, within the context of a simplified case study, and to highlight the main directions for implementing this methodology in business realities.
Design/methodology/approach
Using a simplified case study of an international 3PL company, this study applies a GA developed in RStudio by LLM to generate test scenarios and input data. The GA was optimized to minimize the time and distance of movement in the process of preparing goods for shipment, demonstrating its effectiveness in improving warehouse delivery scheduling.
Findings
The study confirms that the GA, supported by LLM, significantly improves the delivery planning process in the warehouse. Specifically, the implementation of the GA led to notable improvements in scheduling efficiency and a reduction in the distance traveled within the warehouse. These enhancements enable more efficient generation, evaluation and optimization of logistic scenarios. Additionally, the use of LLM greatly facilitates the creation and refinement of complex algorithms like GA, through automation and innovative approaches in logistics.
Research limitations/implications
The study highlights limitations related to data quality, the dynamic nature of logistic operations, computational complexity and the need for generalization of results. It also points out the lack of research in business realities that demonstrate the effectiveness of combining the benefits of LLM and GA in practice.
Originality/value
This paper makes a significant contribution to the literature by demonstrating the capabilities of advanced technologies such as GA and LLM in 3PL logistics. It presents an innovative approach to optimizing logistic processes, offering perspectives for further innovations and automation in supply chain management. It also indicates new opportunities for 3PL companies in terms of improving operational and cost efficiency, emphasizing the importance of continuously seeking innovative solutions in the face of increasing market demands.