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This study aims to examine whether insourcing of processes pays off and verifies key hypotheses regarding the financial ratios of organisations.

This paper randomly selects and then surveys 1996 organisations, of which 9.5% (190) stated that they used insourcing, 1.9% (37) made a decision to implement insourcing in the near future and 88.6% did not use insourcing. Then, for available firm data (100 insourcing firms and 100 firms without it), the financial statements of the surveyed companies were obtained to compare the most important financial ratios. The financial situation was compared at four-time points. The mean and median values of individual indicators were compared with the significance of relevant statistical tests.

A U-shaped curve of financial results in the time of enterprises that implemented insourcing and reverse U-shaped curve for enterprises that did not have insourcing are seen. Thus, the insourcing of processes pays off in the long run.

Limitations exist in the generalisation of the results obtained, due to the limited number of samples qualified for analyses (limited reliable financial data).

The research highlights the importance of effective insourcing projects in the long term.

This study is the first to quantify the financial performance of companies that have used insourcing in comparison with a reference group. This paper defines insourcing and contributes to the growing number of studies on insourcing by bringing attention to the financial outcomes in the long run.

Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The purpose of this paper is to evaluate the efficiency in financial intermediation and the cost efficiency in banking service of credit unions in Brazil, based on essentially accounting variables, and to analyze the temporal evolution of the efficiency of these cooperatives.

With a sample of 315 cooperatives over the period from 2007 to 2014, this research uses a two-stage process: application of regression models with panel data to verify which variables are related to the defined outputs, with the reduction of 31 variables to 8 variables in both models; and application of the data envelopment analysis method to obtain an analysis of credit unions’ efficiency.

The results demonstrate a high level of efficiency in financial intermediation, with low variation over time, associated with a low efficiency in the banking service, in which few cooperatives have remained efficient over time. In addition, the cooperatives with highest efficiency in financial intermediation were also the most efficient in providing services.

This research has some limitations about the capacity of the proxies used to capture the real effect of the variables and assumptions of economic relations resulting in restrictions to generalize the results.

Cooperatives are usually analyzed under just one dimension. By separating the analysis into financial intermediation and banking services, cooperatives that are more efficient in each dimension can be identified, in addition to analyzing the evolution over time. The authors found that efficiency tends to be lower in banking services, and few cooperatives remain at the highest level of efficiency over time in both models.

Credit unions provide an important service in the banking and credit market. Therefore, understanding its operation and the characteristics that influence its efficiency allows a better management of the cooperatives themselves and a greater understanding of this important segment of the financial market.

This study aimed to bridge the gap between the financial measurement of process improvement ideas and Lean Six Sigma measurements. It was required to increase employee engagement in process improvement initiatives.

Through both a practical and theoretical application of the Design for Lean Six Sigma methodology, the researcher was able to design a process and a benefit measuring methodology that was acceptable by finance and aligns with the benefits expected from the elimination of the Lean wastes.

The project found that benefit measurement methodology is not understood by most employees, which leads to a lack of engagement in working on improvements. The result of the study was a model for employees to identify and quantify these benefits. This has resulted in a model for cost-benefit analysis aligning financial costs with non-value add waste costs and cost of poor-quality costs resulting in increased process improvement ideas and activity.

While this study was limited to one company, applying this methodology could benefit any company experiencing the same difficulties.

This is one of the first studies to try and cost the benefits of LSS projects both from an organisational and generic viewpoint.

The employer brand is a crucial intangible asset for companies as it enhances the employer–employee relationship, leading to improved employee performance and overall company outcomes. This paper aims to investigate the contribution of the employer brand to the financial results of companies in southern Europe.

The sample consists of 266 companies operating in southern European countries during the year 2020. Secondary data on employer brand attributes, assessed from the perspective of current employees, were collected from the Glassdoor platform. Financial indicators were obtained from the companies' annual financial reports. The research hypotheses were tested using regression analysis.

The results of the regression analysis support the notion that the employer brand contributes to profitability indicators and management effectiveness indicators of southern European companies. However, the study did not find evidence supporting the contribution of the employer brand to market indicators and financial structure indicators of the observed companies.

This study is one of the first empirical investigations to assess the role of the employer brand as a human capital tool for enhancing the financial performance of companies in southern Europe. The study examines employer brand attributes from the perspective of current employees, who actively participate in shaping the employer brand and the company's image. In contrast to prior research, this study incorporates a more extensive set of financial indicators, categorized into four groups: profitability indicators, management effectiveness indicators, market indicators and financial structure indicators.

The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.

Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.

Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.

The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.

The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.

Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return.

An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews.

This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction.

The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.

For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction problem based on the CSI300 nearby futures by using high-frequency data recorded each minute from the launch date of the futures to roughly two years after constituent stocks of the futures all becoming shortable, a time period witnessing significantly increased trading activities.

In order to answer questions as follows, this study adopts the neural network for modeling the irregular trading volume series of the CSI300 nearby futures: are the research able to utilize the lags of the trading volume series to make predictions; if this is the case, how far can the predictions go and how accurate can the predictions be; can this research use predictive information from trading volumes of the CSI300 spot and first distant futures for improving prediction accuracy and what is the corresponding magnitude; how sophisticated is the model; and how robust are its predictions?

The results of this study show that a simple neural network model could be constructed with 10 hidden neurons to robustly predict the trading volume of the CSI300 nearby futures using 1–20 min ahead trading volume data. The model leads to the root mean square error of about 955 contracts. Utilizing additional predictive information from trading volumes of the CSI300 spot and first distant futures could further benefit prediction accuracy and the magnitude of improvements is about 1–2%. This benefit is particularly significant when the trading volume of the CSI300 nearby futures is close to be zero. Another benefit, at the cost of the model becoming slightly more sophisticated with more hidden neurons, is that predictions could be generated through 1–30 min ahead trading volume data.

The results of this study could be used for multiple purposes, including designing financial index trading systems and platforms, monitoring systematic financial risks and building financial index price forecasting.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

This study explores the benefits of business financial inclusion from the Islamic perspective in Nigeria by selecting Kano state as a case study.

Primary data were generated through semi-structured interviews with experts who comprised professional accountants/consultants and experienced traders. Thematic analysis was applied to examine the data collected. In addition, observations were made in some selected stores and shops to complement the interview results.

The study finds that the benefits of business financial inclusion include recordkeeping improvement, reduction of the risks of bad debts, reduction of the risks associated with cash, enhancing business zakāh for poverty alleviation, sales improvement and business growth, getting supports from government and other development organizations and the provision of employment opportunities.

This study is purely qualitative, and, as such, it has some limitations in terms of generalization.

The practical implication of this study is that the use of electronic payment methods, especially point of sales, enhances the business financial inclusion, which consequently maximizes their wealth and contributes to the reduction of poverty to the barest minimum in the society.

The social implication of the findings is that businesses that are financially included are in a better position to discharge religious, philanthropic and other benevolent activities, such as zakāh, qard hasan, waqf and sadaqah, for the welfare of the ummah.

The study points out the benefits of financial inclusion not only to businesses but also to other members of the society at large.