Robustness Testing Research Articles

Determinants of Firm Value: A Study on Islamic Banking in Indonesia

This study attempts to measure the effect of Islamic corporate governance (ICG) and Islamic social responsibility (ISC) on firm value and to analyse the moderation role of profitability. Data from 12 Islamic commercial banks registered in Indonesia were taken from 2017 to 2021 and analyzed using a panel data regression approach with the GLS approach and model robustness testing using the robust least squares analysis method. The results of this study show a positive effect of ICG on firm value and a negative effect of ISC on firm value. The moderation results show that the interaction between profitability and ICG further strengthens the ICG effect on firm value. The results also reveal a negative effect of profitability on the effect of ISC on firm value. This paper discusses the implications of this research for the existing literature, practitioners, and policymakers.

Ownership property, it investment and firm performance

This paper examines the effects of ownership property on the relationship between IT investment and corporate performance of Chinese listed companies. Previous studies focused on the relationship between IT investment and firm performance. Few studies focused on the factors that affect the relationship. Based on the resource-based view and information asymmetry theory, this paper takes all listed companies in China from 2012 to 2018 as the research sample. We find that IT investment has a significant positive correlation with corporate performance and the ownership property has a negative moderating effect on the positive correlation between IT investment and company performance. We address endogeneity concerns with model regressions and fixed effect model. Finally, using the company performance data with a lag of one period for robustness testing, the results are robust.

The Impact of New infrastructure Construction on Optimization and Upgrading of Industrial Structure

Industrial optimization is needed as China’s economy moves toward high-quality growth. The construction of new infrastructure, driven by new development concepts and patterns, facilitates industrial optimization. This study aims to explore the impact and mechanisms of new infrastructure construction on industrial structure optimization. The index of industrial structure upgrading and the pace of industrial transformation were calculated using panel data from 266 prefecture-level cities, which spanned from 2011 to 2018. This study uses two-way fixed effects and mediation effect methodologies to experimentally investigate the impact of new infrastructure construction on the optimization of industrial structure, while also considering possible endogeneity concerns. We found that new infrastructure building promotes industrial transformation and urban industrial structure upgrading. These results pass robustness and endogeneity testing. However, the impact of new infrastructure construction on industrial structure upgrading varies across cities. There is a significant driving effect in economically larger cities with better traditional infrastructure, and those in the eastern region. Smaller cities and those with inferior infrastructure have less impact. New infrastructure construction optimizes urban industrial structures through technological innovation and professional agglomeration, according to mediation effect study. Diversified agglomeration does not significantly upgrade industrial structures. The limitations of our model include the fact that the data does not describe industrial structural dynamics and it does not apply on other geographic scales. We illuminate the intricate connection between new infrastructure and industry upgrading by including city heterogeneity and the mediating impacts of technical innovation and professional clustering.

Toward low‐carbon sustainable development: Exploring the impact of digital economy development and industrial restructuring

AbstractLow‐carbon sustainable development is considered an essential strategy for achieving economic growth and environmental protection, requiring a fundamental transformation of the industrial structure, including developing clean technologies, promoting energy efficiency, and adopting sustainable production and consumption patterns. Simultaneously, the evolving digital economy is acknowledged as an essential driver in optimizing the industrial structure. Therefore, can digital economy development reshape the industrial structure and lead to low‐carbon sustainable development? The main purpose of this paper is to examine the mediating role of industrial structure upgrading in the relationship between the digital economy and low‐carbon development. Its ultimate purpose is to explore more possible paths to achieve low‐carbon development. This paper builds a regression model based on the data of cities. We found that digital economic development can directly promote low‐carbon sustainable development, a conclusion that still holds after endogeneity discussion and robustness testing. Additionally, digital economy development can promote industrial structure upgrading and thus promote low‐carbon sustainable development, meaning that industrial structure upgrading is an effective mechanism for digital economy development to promote low‐carbon sustainable development. This paper provides empirical evidence for the positive environmental externalities of digital economic development and establishes a basic research framework of “digital economic development → industrial structure upgrading → low‐carbon sustainable development.”

Has the Development of The Digital Economy Reduced the Growth Rate of Carbon Emissions?

Against the backdrop of the "30 · 60" dual carbon target, low-carbon development and the progress of the digital economy are the focus of attention at home and abroad. The digital economy has become an important driving force for high-quality economic development in China. This article studies panel data at the provincial level in China from 2011 to 2018, empirically testing the negative correlation between the development of the digital economy and the growth rate of carbon emissions, and verifying the mechanism effect of green technology innovation, Finally, the situation in the eastern, central, and western regions was discussed through sample analysis and robustness testing was conducted. Based on the above research conclusions, the following insights can be drawn: firstly, improve the speed and quality of digital economy development; Secondly, focus on the development of green innovative technologies.

How exports affect green technology innovation in small- and medium-sized enterprises? Evidence from Chinese companies listed on the growth enterprise market.

Using matched data from China Stock Market and Accounting Research (CSMAR) and Wind databases, this paper explores the impact of exports on the green technology innovation (GTI) of small- and medium-sized enterprises (SMEs). The mechanisms are analyzed through a two-way fixed effects model. First, exports contribute significantly to GTI of SMEs. Second, exports mainly contribute to GTI of SMEs by attracting government subsidies and increasing firms' environmental awareness. Third, from the perspective of heterogeneity, exports significantly positively impact GTI of SMEs especially in medium- and low-technology industries and in eastern China. The impact of exports on GTI is also examined by replacing core variables, modifying the sample for robustness testing, and utilizing both urban river density and distance from the center of the city to the nearest port as instrumental variables for endogeneity test. With the continuous development of international import and export trade, enterprises increase GTI research and development by attracting government subsidies, improving the quality of disclosed information, and increasing environmental awareness.

Automated functional and robustness testing of microservice architectures

Microservice Architectures (MSA) are nowadays largely adopted by companies in several domains to provide on-demand services. The reliability of microservices is fundamental to avoid failures compromising the business functionalities. MSA automated testing is possible thanks to well-defined service interfaces specified in open formats like OpenAPI/Swagger.To support automated MSA functional and non-functional testing, we define a framework that: (i) generates test cases with valid and invalid inputs, and executes and monitors tests; (ii) provides coverage and failure information not only on edge, but also on internal microservices; (iii) has the novel feature of identifying causal relations in observed chains of microservices failures.We abstract the testing process of MSA, present the MacroHive framework and its causal inference engine, compare it experimentally to state-of-the-art tools, and discuss its benefits in the MSA testing process.MacroHive exhibits performance comparable to advanced existing tools in terms of edge-level coverage. However, MacroHive has a better failure rate and provides the unique advantages of giving insights about internal coverage and failures, and of inferring causality in failure chains, evidencing microservices to be improved to increase the whole MSA reliability.

Who Does “Endowment Insurance” Support: The Elderly or Their Grown-up Children?

This research paper seeks to understand whether the current basic endowment insurance policy has properly played the role of supporting the elderly needs through intergenerational support within the family. Theoretically, there are problems of the imbalanced structure of pension security, retirees’ comparatively higher pension and the low-level security of young people’s in-service income, and drawbacks of the existing endowment insurance system, both have a certain causal relationship with “gnawing the old.” Data on China’s family tracking survey in 2016 (CFPS2016), Probit model, IV and PSM robustness testing methods were also used to study the relationship between parents’ pensions and their grownup children’s “gnawing-the-old” behavior. The results show that: (1) Compared with young people from families without pension income, those with pensioned parent(s) will less possibly choose to work; the parents’ financial assistance behavior would restrain the children’s intention to work and increase the possibility of “gnawing the old”; (2) Neither the amount of pension income nor financial assistance given to the children is significantly related to young people’s “gnawing the old”; (3) Young people’s “gnawing the old” behaviors are different according to their parents’ professions and living areas; (4) The gap between parents’ pension income and children’s in-service income also adds to the causes of “gnawing the old.” The policy implications of these findings are discussed particularly the formulation of a scientific mechanism for pension income.

How good can a simple artificial neural network predict the medium reorganization energy and the free energy gap from a steady-state fluorescence spectrum?

Medium reorganization energy, Erm, and free energy gap, ΔG, are key characteristics in determining the photoinduced charge transfer rate. They are strongly related to the width and position of the steady-state fluorescence and absorption spectra of organic dyes in solvents. Steady-state spectroscopy is one of the most standard techniques for studying organic dyes. Here, we present a simple machine learning model for cost-effective prediction the medium reorganization energy and the free energy gap from the steady-state fluorescence spectra. Fluorescence spectra with corresponding reference values of physical quantities are calculated using an explicit mathematical expression that addresses electronic-vibrational transitions, intramolecular and solvent reorganizations. An approach to the separate formation of data sets for training and validation is proposed. Gaussian noise is used in training to improve predictions. This study shows that Erm and ΔG can be predicted with the mean absolute error ∼0.024 eV and ∼0.009 eV, respectively. Robustness testing is performed on the experimental spectra of coumarin-153, coumarin-307, and coumarin-522B in a series of solvents.

Bank branch agglomeration and corporate green transformation: Evidence from China

This paper examines the impact of bank branch agglomeration around Chinese A-share listed firms on their green transformation. The study finds that bank branch agglomeration around listed firms at 5 km, 10 km, and 20 km significantly contributes to green transformation. The result is still valid after robustness testing. According to the mechanism analysis, the agglomeration of bank branches near enterprises facilitates green transformation by reducing financing constraints, increasing green investments, or enhancing green innovation. These findings provide theoretical supplements and policy recommendations regarding the relationship between the development of regional banking institutions and the green transformation of enterprises.

Covid-19 pandemic and firm performance: evidence on industry differentials and impacting channels

PurposeThis study explores the impacts of Covid-19 on the performance of firms operating in different industries, and further discovers suspected impacting channels through which Covid-19 is significantly associated with firm performance.Design/methodology/approachA dataset of 402 listed firms from 2017Q1 to 2021Q4 is proceeded with high dimensional fixed effect (firm-quarter fixed effects) models and difference-in-difference models supported by propensity score matching. A thorough robustness testing procedure with a falsification test with a hypothetical event is applied.FindingsThe study asserts that the pandemic has remarkably hurt the businesses in industries that are more vulnerable to the coronavirus and governmental response policies. Adding to the confirmation of sales and expense channels, new channels – competition and short-term receivables –through which the negative impact of the pandemic is passed on firms is also examined.Originality/valueFirst, this study is to be the first comprehensively investigate and affirm the varying impact of Covid-19 on the business performance of listed firms from different industries in Vietnam, providing additional insight into this research field in Vietnam and emerging economies. Second, the authors examine possible channels paving the way for the impact of Covid-19 on firms' performance and especially explore new channels associated with competition and short receivables. Third, the findings help to form the recommendations for Vietnamese firms, and the study could be replicated for other emerging countries under other similar infectious diseases-driven crises.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0072

The Impact of CEO Change on Enterprise Performance

The chief executive officer (CEO) is the enterprise's leader and plays a crucial role in business growth. Thus, the impact of the CEO changeover on the company and the selection of a suitable replacement are equally crucial considerations. This research utilizes data from Shanghai and Shenzhen-listed corporations. Using China's shares from 2010 to 2019 as the primary sample and earnings per share (EPS) as the performance indicator, we examine the influence of CEO turnover and succession sources on the company's performance. This research examines the pertinent literature and concludes that there are numerous elements that influence corporate performance, such as CEO turnover, firm size, debt ratio, etc. Several control variables are selected to develop an econometric model in order to control the influence of other factors affecting independent variables and dependent variables. This paper focuses on empirical analysis, does descriptive statistical analysis and multiple regression analysis, and employs the PSM-DID model for robustness testing in order to investigate the effect of CEO change on firm performance. After accounting for the endogenous or self-selection bias of the control sample, the study indicated that CEO turnover has a detrimental effect on company performance. From the standpoint of succession types, the corporate performance of listed companies with external successors is inferior to that of publicly traded companies with internal successors. On the basis of the above empirical findings, this study makes related recommendations for the current corporate management practice in China.

Dynamic return connectedness between commodities and travel & leisure ETFs: Investment strategies and portfolio implications

Examining return connectedness between the largest US-based oil and gold ETFs and three major travel & leisure ETFs, we provide substantial value for understanding how investors can diversify sectoral risk. We also compare several portfolio strategies to explore interactive effects. Results indicate a high level of interdependence between gold, oil and the examined ETFs, where the minimum variance portfolio (MVP) is found to be the most efficient. Robustness testing reaffirms the finding that the gold ETF is an important portfolio rebalancing tool to specifically minimise risks associated with travel-related ETFs. Our results have important implications for investors and portfolio managers.

The Impact and Mechanism of Corporate ESG Construction on the Efficiency of Regional Green Economy: An Empirical Analysis Based on Signal Transmission Theory and Stakeholder Theory

The Chinese government’s ongoing endeavors to achieve the “low carbon goals” hold immense importance in global emissions reduction. Nonetheless, reducing emissions will inevitably cause economic losses. Therefore, the pursuit of green economic efficiency is regarded as an effective tool to mitigate the economic losses during emission reduction. Synchronously, the realization of green economic efficiency is essential for sustainable development. With the increasing awareness of regional green development, emphasis companies place on environmental, social, and corporate governance (ESG), which contributes to corporate ESG construction, could become a novel advantage in terms of attracting investors. Additionally, it could have a lasting impact on corporate green technological innovation, thereby enhancing the efficiency. Based on the data of A-share listed companies in China from 2009 to 2019, this study analyzes the effect of corporate ESG construction on the efficiency of regional green economy as well as its mechanism. The research findings demonstrate a significant positive impact of corporate ESG construction on the efficiency of regional green economies. Specifically, each unit improvement in corporate ESG construction is associated with an approximate 0.7% increase in the efficiency of the regional green economy. The conclusion can be drawn after robustness testing. Notably, the effect of corporate ESG construction is more pronounced for companies located in the eastern region, state-owned enterprises, and high-polluting industries. In terms of the underlying mechanism, corporate ESG construction facilitates regional green economic efficiency by fostering corporate green technological innovation. Furthermore, it is observed that environmental regulations have a negative moderating influence on corporate ESG construction, which in turn affects regional green economic efficiency. When examining the decomposed variables of regional green economic efficiency, the impact of corporate ESG construction on regional green scale efficiency is found to align with its overall effect on regional green economic efficiency. This study contributes to the existing research on corporate ESG construction and regional green economic efficiency, offering valuable insights to guide companies in enhancing both aspects. Building upon the conclusions drawn, we will provide policy recommendations from the perspectives of the company itself, corporate investors, and the government. These recommendations aim to facilitate improvements in corporate ESG construction and foster the enhancement of regional green economic efficiency.

Optimization and in-house validation of the analytical procedure for official control of bentonites as aflatoxin inactivators

In Europe, bentonites are allowed as feed additives for aflatoxin mitigation (1m558) provided they have specific mineralogical characteristics and an aflatoxin-binding capacity (BCAfB1) above 90%. BCAfB1 is determined by an official adsorption assay using an aflatoxin solution (4 mg/L) in acetate buffer (pH 5.0) and a bentonite at 0.02% (w/v). To date, the robustness of this method has not been investigated.In this work, we addressed this challenge and performed a robustness study by analyzing six bentonite samples that met the mineralogical requirements for claim code 1 m558. Leading factors selected for robustness testing were (1) preparation mode of bentonite suspension, (2) residual amount of acetonitrile in the test trial, (3) acetate buffer concentration, (4) incubation time, and (5) centrifugation. It was statistically evinced that factors 2 and 5 affected the results. Due to its weakness, the method excluded 4 out of six bentonites to be marketed in EU, being BCAfB1 < 90%. A new protocol was developed by keeping the main experimental parameters of the official assay and was in-house validated. This protocol yielded BCAfB1 > 90% for all test bentonites and showed satisfactory precisions with a RSDI of 3.4% and HorRat < 2. Its validity was proven by the isotherm approach, comparing Langmuir adsorption parameters with BCAfB1 values. Application of the protocol to bentonites other than montmorillonite was demonstrated.

Firm life cycle and cost of debt

Theory provides several channels linking the corporate life cycle and lending risks. Using a sample of 20,307 firm-loan observations spanning 5,076 publicly traded U.S. firms, we find an economically significant relationship between firm life cycle stage and lending spreads. Based on the Owen and Yawson (2010) life cycle stage classification, young firms are expected to pay at least 15 bps more than mature firms, whereas mature firms pay at least 11 bps more than old firms. According to the Dickinson (2011) cash flow classification, firms in the introduction and decline phases pay lending spreads that are 6 and 12 percent greater than firms in the mature phase. We explore omitted variables bias and instrumental variable estimation in robustness testing to alleviate endogeneity concerns. A mechanism analysis shows that credit risk, systematic risk, and idiosyncratic risk follow the corporate life pattern in accordance with loan spreads, suggesting that banks charge a premium to compensate for risk. Our results support the theoretical prediction that structural changes occur as firms evolve across the corporate life cycle.

Validation of the KangarooSci® Aerobic Count Plate for the Enumeration of Meosphilic Aerobic Bacteria in Selected Foods and on Stainless Steel Environmental Surfaces: AOAC Performance Tested MethodSM 062301.

The KangarooSci® Aerobic Count Plate is a sample-ready culture medium system, for direct counting of aerobic bacteria colonies after 48-72 h of incubation. The KangarooSci Aerobic Count Plate was evaluated for AOAC® Performance Tested Methods SM certification. The KangarooSci Aerobic Count Plate (ACP) was evaluated through matrix studies and product consistency/stability study and robustness testing. For the matrix study, nine food products (nonfat dry milk powder, fresh raw bovine milk, pasteurized liquid bovine milk, fresh raw ground beef, frozen uncooked chicken breast, cooked shredded pork, apple juice, ice cream, and fresh strawberries), and one environmental surface (stainless steel) were evaluated following the KangarooSci ACP product instructions and compared to the ISO 4833-1:2013-pat 1, Microbiology of food and animal feeding stuffs-Horizontal methods for the enumeration of microorganisms-Part 1: Colony count at 30 °C by the pour plate technique reference standard. The product consistency and stability testing evaluated three separate production lots of the KangarooSci ACP. The robustness testing examined three test parameters, volume of sample plated, incubation time, and incubation temperature using a factorial study design. Results from the matrix study demonstrated equivalent performance between the KangarooSci ACP and the ISO 4833-1:2013 reference standard. The product consistency and stability testing showed that the performance of the assay was equivalent over time up to 12 months and between production lots. Minor changes to the operational test conditions showed no significant impact on performance during the robustness testing. The KangarooSci ACP is an effective method for aerobic plate count for all matrixes evaluated. The KangarooSci Aerobic Count Plate allows for fast, reliable enumeration of aerobic bacteria. Utilizing the alternative method takes up less space in incubators, requiring no sample spreader, and requires less consumables compared to the reference method.

Research on the implementation path of industrial structure optimization in Fujian Province under the goal of “double carbon”

Abstract Facing the dual pressure of domestic environmental pollution and international climate change mitigation, China, the world’s largest emitter of carbon emissions, has proposed a “double carbon” target of 3060. Fujian Province is a clean energy province and a major economic province in southeastern China, with inherent energy conservation and emission reduction advantages. However, as industrialization is still in progress and urbanization is accelerating, the problems of low industrial level and sloppy development are still prominent, and the future low-carbon transformation will be difficult and long. Based on the theory of industrial structure optimization and the theory of low carbon economy, this paper analyzes the influence mechanism of industrial structure optimization on carbon emission from three perspectives: efficiency improvement, technological progress, and structural adjustment. Secondly, an econometric model is constructed by combining the environmental Kuznets curve, and the time series data of Fujian Province from 2000-2021 are analyzed empirically to derive the optimization path of industrial structure on carbon emissions in Fujian Province through co-integration analysis, multiple regression, mediating effect analysis, and robustness testing methods. The results of this paper show that from the structure of energy consumption in Fujian Province, coal and oil consumption account for 72% of the total consumption, which is the main cause of carbon emissions in Fujian Province. The mediating effect and stability analysis of the optimization path through the benchmark regression model shows that the p-value variance is 0.0862, and there is no significant difference between them. The optimization path proposed in this paper has significant utility for carbon emission reduction, improves the efficiency of energy use, strengthens the introduction of FDI and industrial structure optimization in various regions of Fujian Province in a targeted manner, and provides a reference for decision-making for global industrial structure optimization and upgrading.

Returnee executives and digital transformation: an inverted U-shaped relationship

ABSTRACT Digital transformation has been an increasingly critical issue in the digital era. The paper expands research on corporate digital transformation drivers and examines executive contextual factors. A text mining method creates digital transformation indicators, and a nonlinear model is used to empirically analyse the impact of returnee executives on corporate digital transformation using Chinese A-share listed companies from 2012 to 2021. After robustness testing, returnee executives and company digital transformation have an inverted U-shaped, nonlinear relationship. Further studies show that financial restrictions strengthen the inverted U-shaped association between returnee executives and digital transformation, while financial position weakens it. The findings are of great reference and implication for promoting the digital transformation of enterprises.

Integrated Modelling and Control of Linear Actuator Based Automatic Pedal Pressing Mechanism for Low-Speed Driving in a Road Traffic Delay

Sitting in traffic congestion for hours in a posture that requires recurrent actions of manually pressing the pedal and braking excessively can result in fatigue, especially on the driver's leg and back. This fatigue can have long-term implications and adversely affect the driver's health. Thus, this paper aims to model and develop a control system that utilizes a linear actuator to replace the leg activities involved in pressing and releasing the brake pedal. This approach, combined with the implementation of a PID controller, offers a novel solution to control the vehicle speed by integration with the linear actuator that focus on low-speed driving condition. The design process begins with creating a 3D model using SolidWorks to visualize the movement of the linear actuator and Pedal subsystem. This model is then connected to Matlab-Simulink, where a PID controller is implemented and integrated into the electrical circuit to control the actuator's movement. Integration with the vehicle dynamic model enables a comprehensive analysis of the system's behavior on the vehicle dynamics. This research compares the trial and error method with the Matlab tuner for implementing the PID controller. The performance of the system will be evaluated based on the steady state error, overshoot, rise time, and settling time. The results demonstrate that the Matlab tuner outperforms trial and error method by achieving a faster response and significantly reducing steady state error during robustness testing. With the integration of the linear actuator, the system is capable of tracking the desired speed and has the potential to replace the leg activities involved in pressing and releasing the brake pedal. For future work, validating the proposed mechanism with a physical prototype of the linear actuator and pedal using hardware-in-the-loop techniques poses a challenge, as hardware constraints may vary with different environments.