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This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) with artificial intelligence (AI).

The study identified the tailoring department as the department with maximum defects by using voice of customer and critical to quality tools. An AI-integrated Six Sigma approach was applied to identify and eliminate nonproductive stages, and a new facility layout was designed to enhance productivity and customer satisfaction.

The use of the factor rating method and simulation using Arena software led to an improved sigma level from 1.597 to 2.237, representing an increment of about 40%. Additionally, the defects per million opportunities reduced from 461,538 to 230,769. The study can help production industry management to optimize facility layouts and improve overall production line efficiency.

This study addresses the lack of published research on the use of an integrated approach of Six Sigma DMAIC with AI in the retail and distribution sector of Saudi Arabia, particularly for small and medium-sized enterprises (SMEs). The study demonstrates how this approach may significantly boost SMEs’ performance and provides a basis for future research in this area.

This study provides a practical example of how an integrated approach of Six Sigma DMAIC with AI can be used in the retail and distribution sector of Saudi Arabia to enhance operational excellence and continuous improvement. The study highlights the potential benefits of this approach for SMEs in the region and provides a framework for future research.

The purpose of this paper is to propose a method that can calculate the transportation infrastructure network service capacity enhancement given by planned transportation infrastructure projects construction. Managers can sequence projects more rationally to maximize the construction effectiveness of infrastructure investments.

This paper designed a computational network simulation software to generate topological networks based on established rules. Based on the topological networks, the software simulated the movement path of users and calculated the average travel time. This software allows the adjustment of parameters to suit different research objectives. The average travel time is used as an evaluation index to determine the most appropriate construction sequence.

In this paper, the transportation infrastructure network of Sichuan Province in China was used to demonstrate this software. The average travel time of the existing transportation network in Sichuan Province was calculated as 211 min using this software. The high-speed railways from Leshan to Xichang and from Xichang to Yibin had the greatest influence on shortening the average travel time. This paper also measured the changes in the average travel time under two strategies: shortening the maximum and minimum priorities. All the transportation network optimisation plans for Sichuan Province will be somewhere between these two strategies.

The contribution of this research are three aspects: First, a complex network analysis method that can take into account the differences of node elements is proposed. Second, it provides an effective tool for decision makers to plan transportation infrastructure construction. Third, the construction sequence of transportation infrastructure development plan can effect the infrastructure investment effectiveness.

This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

The study aims to analyse the role of digitisation in accounting in enhancing the overall effectiveness of accounting functions. To achieve this, the study provides empirical evidence from the stakeholder’s perspective of digitisation of accounting, auditing, reporting and regulatory compliance procedures.

The study has applied a quantitative approach to identify the thoughts of auditors, accountants and academicians on the impact of digitalised accounting applications on accounting functions. The data was collected by administering an empirical study and a sample of 482 professionals from the accounting, auditing and academic sectors. To analyse and interpret data descriptive statistics, structured equation modelling and mediation analysis has been used.

The finding of the study signifies the relevance of digitalised accounting applications in accounting functions and reveals that there is a significant impact of digitalisation on accounting, auditing, reporting and regulatory compliance aspects of accounting functions. The outcome of the study explores that a digitalised accounting system reduces possible errors and improves the accuracy and transparency of the system.

The study highlighted the importance of developing new methods and techniques that can be used in practice. This indirectly advocates the inclusion of such concepts in accounting curricula to emphasise the need to understand the challenges and opportunities created by digitisation. Furthermore, the study will become a motivation to scholars who intend to explore different areas through which new technologies can be adopted to transform traditional accounting systems.

The contributions of the current study have implications that the adoption of digitised accounting enhances economic efficiency through a reduction in accounting costs, and enhanced accuracy that leads to the elimination of penalties and litigations for non-compliance with regulatory authorities. This indirectly impacts positively on the financial health of the business organisations and economies at large. This implication becomes greater evidential support to the organisations which are yet to plan the adoption and implementation of digital tools in their organisation for accounting functions.

Digitalisation is a relevant part of the accounting function to improve efficiency and accuracy. Since accounting and auditing practitioners struggle to control the accuracy and efficiency of transactions. Furthermore, the outcome of the study assists organisations in gaining real-time access to financial data, transforms workflows and empowers management to make timely informed sound decisions, optimise resource allocation, efficient regulatory compliance and so on.

In China, engineering insurance has been questioned as not being beneficial as expected. This paper seeks to further understand how China's engineering insurance industry functions and to provide a macro perspective explanation for engineering insurance's underdevelopment.

Three industrial organization hypotheses were extended to the engineering insurance context: structure conduct performance (SCP), relative market power (RMP) and efficiency structure (ES) hypotheses. This paper employed the Generalized Method of Moments (GMM) and Data Envelopment Analysis (DEA) bootstrap to test the hypotheses using panel data from 2008 to 2017.

The results suggest that the SCP paradigm is validated in China's engineering insurance market, indicating a concentrated market where the welfare of consumers (e.g. owners, contractors and designers) may be eroded. Several factors are identified to have significant impacts on engineering insurers' performance, such as the investment return, percentage of engineering business, the ratio of outstanding claims, the number of large contractors, market rivalry and entry barriers.

Despite the sheer size of China's construction industry and the urgent need to improve risk management, the insurance industry that serves construction firms engineering insurance is underdeveloped. Engineering insurance is yet to be understood from a macro perspective, which may reveal the underlying reasons for engineering insurance's underdevelopment. The industrial organization theories provided a theoretical framework to test the functioning of this specific industry. The disaggregated data (engineering line specific) is employed to ensure effective regulation and policymaking.

This investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.

In this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

The provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.

In this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

This paper aims to assess whether incubation affects the technical efficiency of innovative firms after entering the market. The study of efficiency allows firms to understand how well resources have been used in production processes. The research intends to contribute to the literature on the performance of incubated firms.

This study estimates the relative efficiency of innovative firms adopting a DEA-based two-stage semi-parametric method. Incubation, firm age and initial capital are used for explaining the relative performance of previously incubated firms compared to non-incubated ones over a six-year period of activity. This research focuses on Italian innovative firms using a large sample of companies.

Results show that incubators have a positive and significant effect on efficiency for firms that have been in the market for more than two years. Efficiency also improves with age and with the level of initial capital of the firm.

This analysis is limited to the quantitative dimension of inputs as reported in the balance sheets, without qualitative considerations.

Findings enhance firms' understanding of the role of incubators as neutral places to develop a business culture of efficiency. From an empirical standpoint, this study provides useful insights to start-uppers who intend to attend incubation programs. Overall, incubators matter to the extent that they enable new firms, net of those that fail to survive in the first two years of activity, to improve their efficiency in the use of inputs. This research also suggests incubators consider the start-ups’ potential of being efficient.

Findings provide tips to policymakers when they are called upon to propose funding programs to support prominent firms entering the business scalability.

This study contributes to the literature on the relative performance of post-incubated firms, highlighting the efficiency frontier analysis. This methodological approach is relatively new in this field. It allows researchers to study the innovative firms' performance in relative terms, that is with respect to the input level. It integrates the performance-based with efficiency frontier analysis. Also, this study reinforces the idea that incubators prepare start-ups to develop capacities and managerial skills, which will be useful in post-incubation life to improve their cost competitiveness.