Search results

Regulation is critical for sustainable microfinance sector growth. Under this premise, the study aims to examine the different regulatory noncompliance (RNC) practices prevalent in the operations of microfinance institutions (MFIs) at the ground level.

Both the quantitative and qualitative (observations, interviews and focus group discussions) techniques are used to extract the findings.

The study highlights the different RNC practices exercised by the loan officers at the field level in their microfinance loan disbursements.

This study is based on the primary data collected from microfinance clients. The arguments put forth for the RNC practices are extracted from direct personal interviews with the loan officers and the clients. The role of various dilemmas/circumstances of the loan officers and the beneficiaries that implicate the MFIs in RNC is highlighted.

The purpose of this paper is to analyze the impact of the cost of microfinance intermediation on borrowers’ loan size. The identified transaction cost and credit risk factors tell about what a lender takes into accounts while screening and allocating loan amounts to the borrowers, where the lender has limited information about the client’s ability to repay.

The analysis is based on the primary data collected from a sample of 498 microfinance institutions (MFI) linked group clients covering two microfinance leading states of India.

Empirical findings suggest that the cost of microfinance intermediation has an impact on borrowers’ loan size. To reduce the cost, the MFIs lend big loans to clients having a high income, assets, land size, lower informal borrowings and having longer loan experiences. In MFI lending, the younger and less educated people are the ones who demand bigger loan amounts. The geographical distance of borrowers’ location from MFI offices, group size and interest rate are the other factors that influence the loan size.

The past empirical works seem to have not focused on how the cost of microfinance intermediation creates loan size variation among the borrowers in joint liability group lending. The endogeneity problem has not been resolved. The present article thus identifies the factors that influence the individual member loan size by using two-stage least squared regression to tackle the issue of endogeneity.

Digitalization is one of the major factors that fosters economic growth across the world. However, the level of digitalization varies significantly between developed and developing countries, with the latter often lagging behind. To bridge this gap, it is crucial to pinpoint the drivers of digitalization, specifically from the macroeconomic and country-level governance dimensions. Therefore, this study aims to investigate the determinants of digitalization, particularly for countries in Asia and the Pacific region.

Our study utilizes unbalanced panel data from 46 Asian and Pacific countries for the period of 2001–2021. Initially, we analyzed the data using conventional econometric methods, such as pooled ordinary least squares (POLS), random-effects model (REM) and fixed-effects model (FEM). Moreover, we employed endogeneity-corrected techniques and alternative proxies to enhance the robustness and reliability of our findings.

Our findings reveal that economic development progress, government expenditure relative to country size and political stability are key drivers of digitalization. In contrast, corruption at the country level emerges as a significant impediment. Notably, our results remain robust to endogeneity-corrected techniques and alternative proxies of digitalization. Overall, these insights can inform policymakers, helping them to understand the macroeconomic and governance factors shaping digitalization and guide their decision-making toward effective policy interventions.

This study’s empirical findings add significant value to the existing literature by quantifying the impact of macroeconomic and governance factors on digitalization in selected countries. This offers valuable insights for policymakers, particularly in nations with lower levels of digitalization.

This work aims to review past and present articles about data-driven quality management (DDQM) in supply chains (SCs). The motive behind the review is to identify associated literature gaps and to provide a future research direction in the field of DDQM in SCs.

A systematic literature review was done in the field of DDQM in SCs. SCOPUS database was chosen to collect articles in the selected field and then an SLR methodology has been followed to review the selected articles. The bibliometric and network analysis has also been conducted to analyze the contributions of various authors, countries and institutions in the field of DDQM in SCs. Network analysis was done by using VOS viewer package to analyze collaboration among researchers.

The findings of the study reveal that the adoption of data-driven technologies and quality management tools can help in strategic decision making. The usage of data-driven technologies such as artificial intelligence and machine learning can significantly enhance the performance of SC operations and network.

The paper discusses the importance of data-driven techniques enabling quality in SC management systems. The linkage between the data-driven techniques and quality management for improving the SC performance was also elaborated in the presented study.

The purpose of this paper is to present a road map to implement Lean-Kaizen concept using value stream mapping (VSM) to identify hidden continuous improvement opportunities in a small and medium-sized enterprise (SME) located at the non-capital region of India.

From the collected data, a current state map was prepared that indicated the current operating situation of selected SME. The takt time was calculated and those processes which attained higher cycle time (C/T) than takt time were identified. The continuous flow processing was achieved by adjusting C/T of each process and supermarket pull system was developed to control the production at the workstations. Finally, a future state map was developed that served as a guide for future lean activities. Few problems were identified to realize the future state. The “5-why” analysis was used for identifying root causes of these problems and Kaizen events were proposed as solutions. In this case study, one Kaizen event was identified in which brainstorming technique was used to control the variation caused by unorthodox fixture design for clamping and de-clamping of case product and thus eliminated non-value-added activities performed by the operator on a milling machine.

Before and after implementation of value stream map, the data obtained were analyzed and eliminated rework time, reduced inventory level, reduced lead time and C/T, improved productivity and product quality are presented as finding. Lean-Kaizen provides a better chance for every individual of the industry to have a hand in achieving organization’s goals to attain continuous progress in productivity and quality of the product. Even good understanding of the concept of lean tools and techniques by SMEs, the employee willingness and motivation to identify and eliminate wastes are found feeble.

This study is among best practices to identify hidden improvement opportunities in the regular production of the product to increase productivity and improve quality using value stream map. The research paper gives useful understandings to the lean implementers, Kaizen identifiers, consultants and researchers.

In global scenario, many organizations own supply chains, which operate in different countries. The performance of these supply chains, owned by the same organization must be same if they operate in countries with similar economical, political, and social conditions. In this paper, an effort has been made to propose a methodology for the internal benchmarking to reduce the variability in performance among supply chains of same focal firm. The proposed methodology of internal benchmarking for assessment of supply chain performance demonstrated through a case supply chain.

A case of global supply chains is presented in which a focal firm owns three supply chains operating in three different countries. In order to assess and improve the performance of these supply chains relative to each other, a benchmarking methodology is proposed.

An extensive use of performance value analysis (PVA) and strength, weaknesses, opportunities, and threats (SWOT) analysis provided good diagnosis of supply chains. This analysis can be very useful in leveraging the supply chain drivers of various supply chains belonging to same focal organization and hence bring performance of all the supply chains at the same performance level.

According to the authors' knowledge, there is no paper in the literature, which discusses the application of PVA and SWOT analysis for internal benchmarking in supply chain management and it is believed that it will be useful for supply chain managers to apply such tools to lead global development in their supply chains.

This study aimed to investigate the suitability and cost-benefit of using copper tailings as partial replacement of sand in concrete production. The study was motivated by the accumulation and non-use of copper tailings in dams among them tailing dam 25 also known as TD 25 in Kitwe city of the Copperbelt province in Zambia that take up approximately 111 hectares of unused land.

Laboratory experimental approach of concrete production based on water/cement ratios of 0.3 and 0.5 was used because this was an exploratory study designed to establish the primary performance of concrete. In total, 30 concrete cubes were cast based on the two water-cement ratios. In total, 0% to 30% partial sand replacement with copper tailings was used in both mixes with the 0% copper tailings replacement being the control mix and reference point. Other concrete tests included workability, density, compressive strength and element composition analysis.

Results revealed that copper tailings from TD 25 were suitable for partial replacement of sand in concrete. Thirty per cent of sand replacement with copper tailings was established as the maximum replacement amount to produce optimum compressive strength values from both mixes. The drier mix of 0.3 water-cement ratios produced higher compressive strength results of 23 MPa at 28 days of concrete curing with 2.34% as optimum concrete cost reduction.

The research results provide the cost-benefit analysis and savings that can be attained from using cheaper copper tailings based concrete. The study further provided the quantity of land available for development arising from absorption of copper tailings as a sustainable construction material. The local authority now has statistics and numerical values that it can use to absorb copper tailings as a concrete raw material.

The study provides guidance on optimum concrete grade produced and cost reduction details of copper tailing-based concrete to support for local authorities in suitable land wand waste management using real data.

The purpose of this paper is to develop a set of key performance indicators (KPIs) for agile manufacturing (AM) and to propose a methodology for its performance evaluation.

The proposed methodology was developed using fuzzy analytic hierarchy process (FAHP) and performance value analysis (PVA) to evaluate and analyze the AM performance. The FAHP is applied to determine the importance of KPIs, and PVA is used to evaluate AM performance.

The proposed methodology is applied to an Indian auto component manufacturer, and it is observed that there is an improvement of performance along the timeline.

The proposed approach is generic in nature and can be applied to different agile business environments for performance evaluation.

This study provides insights into the AM performance evaluation. The managers can establish the impact of each significant area (SA) on AM and each KPI on its corresponding SA by capturing their manufacturing environments.

Although many issues related to AM have been widely researched, only a few studies have been carried out to quantify, analyze and evaluate the AM performance in the Indian manufacturing environment. The proposed model has the ability to capture the performance of AM along the KPIs to draw fruitful conclusions.

The purpose of this paper is to investigate the existing literature on agile manufacturing (AM) to pinpoint critical success factors (CSFs) affecting the successful implementation of agile manufacturing systems.

The study focused on empirical articles published in peer-reviewed journals from 1991 to 2019 (July). In total, 37 empirical studies were shortlisted for analysis as the reliability and validity of the constructs were critically tested using various statistical methods. Further, “Pareto analysis” tool was employed to sort and arrange the factors critical for smoother and effective implementation of AM, in descending order according to their frequency of occurrence.

The present work scrutinizes 37 research papers, resulting in 33 CSFs that affect AM implementation. Using Pareto analysis, 8 CSFs are regarded as “vital few,” which account for 82.66 percent of occurrence, and the remaining 25 CSFs are regarded as “useful many,” which account for 17.34 percent of occurrence. The managers must focus on successful deployment of “vital few” CSFs, as they are more critical in achieving business excellence through the successful implementation of AM, in comparison to other 25 “useful many” CSFs.

To the best knowledge of authors, this work is the first attempt to employ Pareto analysis for critically analyzing a wide range of AM CSFs studies. The findings of this study will assist researchers and managers in AM implementation in a more smoother and effective way in manufacturing industries.