Search results

This study examines the moderating role of information sharing on the effect of lead-time management on the performance of firms in the Zimbabwean motor industry.

Data were collected using Likert-based structured questionnaires from a sample of 105 employees in Zimbabwe. In addition, Pearson Correlation, Linear Regression and Moderation Regression analysis were employed to test the relationship between study variables.

The study found that fixed lead time, preprocessing lead time, processing lead time and postprocessing lead time significantly influence the performance of firms in the motor industry. The results also demonstrate that information sharing moderates the effect of lead-time management on firm performance in the motor industry.

Firms in the motor industry should establish long-term relationships with their suppliers and implement effective communication channels for timely and frequent information exchange regarding production schedules, inventory levels, quality standards and potential disruptions.

The current study aims to contribute to the scientific discourse on lead-time management, information sharing and performance in the motor industry. Furthermore, it extends knowledge on the performance of the motor industry in the African region.

The purpose of this paper is to analyze the applicability of lean accounting and throughput accounting in a company with considerable investments in advanced manufacturing technology (AMT).

The paper compares lean accounting and throughput accounting with the traditional accounting system the company is using today. The authors investigate the differences between the three alternative approaches and use a case study approach to illustrate the effects of applying different modern accounting approaches in a complex manufacturing setting.

Pair-wise comparisons of the three approaches provide some interesting cost information as to the role of bottlenecks and value streams.

The specific results of this study are limited to the case company, but can hopefully contribute to further research on how to combine lean and throughput accounting for mixed manufacturing environments, involving both value streams and bottlenecks.

Lean and throughput accounting provide other perspectives on cost information to traditional accounting, and can therefore be used in combination. The authors identify some issues and challenges involved in using lean accounting and throughput accounting in an AMT company.

This paper contributes with a comparison of traditional, lean, and throughput accounting in a specific industrial setting characterized by AMT and complex manufacturing.

Reviews a critical aspect of job shop scheduling research, namely the decision regarding release timing of orders to the manufacturing shopfloor. Covers articles specifically addressing the order release problem; the information should prove helpful for researchers employing order release policies in their research. The release decision literature is classified into three areas: descriptive studies including case and survey research, analytical or optimization‐based research, and simulations of theoretical and empirically derived job shops. Presents tables describing the release rules and summarizing the characteristics of the simulation research. Identifies a number of topics within the order release research area in need of further investigation, including the comparison of larger sets of release rules, the use of more realistic simulation models such as the dual resource constrained job shop model, the need for further empirical identification of release policies, and the use of release policies that consider dynamic shop conditions.

Theory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of literature is needed to summarize the key findings of various researchers. Such a review can provide a direction to the researchers and academicians interested in exploring the application of TOC in the healthcare sector. This paper aims to review the existing literature of TOC tools and techniques applied to the healthcare environment, and to investigate motivating factors, benefits and key gaps for identifying directions for future research in the domain of healthcare.

In this paper, different electronic repositories were searched using multiple keywords. The current study identified 36 articles published between January 1999 to mid-2021 to conceptualize and summarize the research questions used in the study. Descriptive analysis along with pictorial representations have been used for better visualization of work.

This paper presents a thorough literature review of TOC in healthcare and identifies the evolution, current trends, tools used, nature of services chosen for application and research gaps and recommends future direction for research. A variety of motivating factors and benefits of TOC in healthcare are identified. Another key finding of this study is that almost all implementations listed in literature reported positive outcomes and substantial improvements in the performance of the healthcare unit chosen for study.

This paper provides valuable insight to researchers, practitioners and policymakers on the potential of TOC to improve quality of services, flow of patients, revenues, process efficiency and cost reduction in different health care settings. A number of findings and suggestions compiled in the paper from literature study can be used for diagnosing, learning and making substantial changes in healthcare. The methodologies used by different researchers were analysed and combined to propose a generic step by step procedure to apply TOC. This methodology will guide the practising managers about the appropriate tools of TOC for their specific need.

Good health is always the first desire of all men and women around the globe. The global aim of healthcare is to quickly cure more patients and ensure healthier population both today and in future. This article will work as a foundation for future applications of TOC in healthcare and guide upcoming applications in the booming healthcare sector. The paper will help the healthcare managers in serving a greater number of patients with limited available resources.

This paper provides original collaborative work compiled by the authors. Since no comprehensive systematic review of TOC in healthcare has been reported earlier, this study would be a valuable asset for researchers in this field. A model has been presented that links various benefits with one another and clarifies the need to focus on process improvement which naturally results in these benefits. Similarly, a model has been presented to guide the users in implementation of TOC in healthcare.

The purpose of studying digitization transformation of the supply chain is to understand how digital technologies and processes are changing the way supply chains operate and to identify the opportunities and challenges associated with this transformation. Studying digitization transformation of the supply chain is important because it can help global businesses in identifying the best practices in supply chain management (SCM) systems and enhance supply chain performance. Hence, this research study is contributing in revealing the outcomes of digital inclusiveness in overall SCM for the growth of retail and e-commerce based platforms.

This research is using both descriptive and explanatory research designs to provide a comprehensive understanding of the problems in SCM. Descriptive research provides a detailed description of the characteristics of the population under study, while explanatory research identifies the causal relationships between the variables. Descriptive research has helped us to develop hypotheses about the relationships between variables that can be tested using explanatory research. Explanatory research has been used to validate the findings of descriptive research. By using both descriptive and explanatory research designs, our research design has increased the generalizability of our findings.

According to this study, businesses intend to change their supply chain strategies after the wake of competitive era to make them more robust, sustainable and collaborative with suppliers, customers and stakeholders by investing more in SCM technology like Blockchain, AI, analytics, robotic process automation and data control centers. This study evaluates the impact of digitization on supply chain systems. This includes assessing the benefits of digitization and identifying the factors that contribute to successful implementation. This research is studying the role of data analytics in SCM and how it can be leveraged to improve efficiency, reduce costs and increase transparency.

The study highlights the importance of adopting digitization in supply chain systems to improve supply chain robustness, sustainability and collaboration with stakeholders. This study's emphasis on data analytics in SCM presents an opportunity for businesses to gain insights into their supply chain systems and make data-driven decisions. This can enhance efficiency, reduce costs and improve overall supply chain performance. The study's focus on SCM technology and data analytics may overlook other factors that contribute to successful SCM, such as organizational culture, human resources and supply chain governance.

This study will complement to the existing body of information, management theory and practice and will benefit all. The research work is original and can be implemented worldwide to promote digitization in SCM for smooth transactions in the entire chain of wholesalers, retail distributors and customers.

The purpose of this paper is to investigate supply chain management practices related to flexibility, value chain and capabilities. It describes an exploratory study to examine the interrelated factors to propose a research framework.

A comparative case study was conducted on several manufacturing organizations in the electrical and electronic industry, investigating the business drivers and response effect of a flexible value chain.

In general, all the organizations enhanced their manufacturing flexibility components with supply and logistic networks in order to be responsive to customers and gain tangible benefits. The core flexibility of the value chain can be defined from operational, supply and logistics perspectives where different levels of integration and implementation strategies offer different levels of flexibility response to volume and product mix.

Research through case survey requires further empirical investigation to quantify the determinants and the significance of the relationship theorized. However, the findings confirmed the practical aspect of manufacturers to consider flexibility in designing their value chain within the industry.

The paper highlights the fact that local manufacturers value the flexibility aspect of supply chains to stay competitive during demand uncertainties and being responsive to customers.

This paper aims to develop a lean manufacturing road map for industrial firms by selecting the appropriate lean tools relying on the predefined strategic objectives and the firm constraints. It also illustrates how to prioritize these tools considering their interrelationship.

Relying on the predefined strategic objectives, operational objectives can be set by using the balanced scorecard (BSC). Afterwards, the theory of constraints (TOC) is introduced to investigate the manufacturing system and to determine its constraints. For these constraints, the principle of fault tree analysis (FTA) is used to determine their root causes. Consequently, lean manufacturing tools/initiatives can be proposed. Finally, the fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) method is implemented to prioritize these initiatives and to construct a suitable lean road map by managing experts’ knowledge.

The practical results indicate that diagnosing the manufacturing system and managing experts’ knowledge to select the appropriate lean initiatives, and prioritizing these initiatives relying on the understanding of their interrelationship could support achieving the strategic targets without consuming extra time or resources.

The study is limited to manufacturing firms. Besides, it reinforces the need for investigating the effectiveness of the proposed approach on service sectors.

The study provides a methodology with a real application, to manage experts’ knowledge for developing an effective lean improvement road map. The methodology could be adopted by any manufacturing firm.

The study supports decision makers of a firm to select the improvement initiatives by an original structural approach, which integrates BSC, TOC, FTA and fuzzy-DEMATEL. Besides, the interrelationships among the selected lean initiatives are considered, and results show the importance of analysing these interrelationships during the construction of the lean improvement plan. Moreover, its effectiveness and applicability are validated via a practical case study.

This paper introduces a new hybrid evolutionary algorithm (EA) for continuous global optimization problems, called estimation of distribution algorithm with local search (EDA/L). Like other EAs, EDA/L maintains and improves a population of solutions in the feasible region. Initial candidate solutions are generated by uniform design, these solutions evenly scatter over the feasible solution region. To generate a new population, a marginal histogram model is built based on the global statistical information extracted from the current population and then new solutions are sampled from the model thus built. The incomplete simplex method applies to every new solution generated by uniform design or sampled from the histogram model. Unconstrained optimization by diagonal quadratic approximation applies to several selected resultant solutions of the incomplete simplex method at each generation. We study the effectiveness of main components of EDA/L. The experimental results demonstrate that EDA/L is better than four other recent EAs in terms of the solution quality and the computational cost.

This paper provides an overview of a series of research projects investigating the diffusion and appropriation of technologies for production and inventory control (PIC). These technologies are referred to, collectively, as production and inventory control systems (PICS) though also appear under a number of other names (for example, computer‐aided production management). PICS are information technologies used, predominantly by operations management or logistics personnel in manufacturing industry, to plan and schedule production runs and materials handling so that materials are available when required for production without holding unnecessary inventory. Typically, though not always, the technologies are computer‐aided. Like other technologies, they involve a significant amount of organisational as well as technical innovation (c.f. Damanpour, et al, 1989).

The world has witnessed three major individual revolutions until now. We are in the fourth industrial revolution, and there are technological breakthroughs that have not been seen before. Responding fast to changing consumer expectations in a competitive climate brought on by globalization has become a global reality, requiring enterprises to alter their manufacturing systems. The incorporation of machines that can interact and make decisions into production has altered the manufacturing processes. The application of the Industry 4.0 revolution to manufacturing processes has paved the way for the development of smart factories. Production may be made 24 hours a day in these factories where productivity grows with applications such as the internet of things (IoT), cyber-physical systems, augmented reality and artificial intelligence. All applications utilized in smart factories boost productivity and reduce costs and human error rates. Countries should undergo change in order to adapt to the competitive climate established by Industry 4.0, in which the entire world lives. Many industrialized countries have taken significant strides in this direction, including this process into their national policies. Turkey's ability to adapt to Industry 4.0 technologies in a digitalized competitive environment, as well as swiftly grow smart factory applications in altering production processes, is critical to its global economic standing.