In today’s big-data era, enterprises are able to generate complex and non-structured information that could cause considerable challenges for CPA firms in data analysis issue improper audited reports within the required period. Artificial intelligence (AI)-enabled auditing technology not only facilitates accurate comprehensive firms, but is also a major breakthrough auditing’s new environment. Applications of an AI-enabled technique external can add efficiency, increase financial reporting...

In a highly intertwined and connected business environment, globalized layout planning can be an effective way for enterprises to expand their market. Nevertheless, conflicts contradictions always exist between parent subsidiary enterprises; if they are in different countries, these become especially problematic. Internal control systems supervision management seem particularly important when aiming align subsidiaries' decisions with enterprises' strategic intentions, such undoubtedly...

This study examines the impact of corporate social responsibility (CSR) news reports on operating performance forecasting using a large database publicly-listed electronics firms in Taiwan. Applying text mining techniques and latent topic modelling, we construct measure intensity CSR-corpus index (ICSRI), which can compress tremendous amounts CSR textual information content into synthesized meaningful dimensions. By doing so, are able to break down multiple dimensions then examine...

It is widely recognized that a firm’s well-established corporate governance (CG) has considerable impact on its social responsibility (CSR) performance. How to determine the main trigger among CG’s indicators for strengthening CSR performance thus an urgent and complicated task due (i.e., CSR) multi-dimensional numerous perspectives. In order solve this critical problem, study breaks down into four dimensions further examines of each dimension by joint utilization rough set theory (RST)...

This study establishes a decision-making conceptual architecture that evaluates decision making units (DMUs) from numerous aspects. The combines financial indicators together with variety of data envelopment analysis (DEA) specifications to encapsulate more information give complete picture corporate’s operation. To make outcomes accessible non-specialists, multidimensional scaling (MDS) was performed visualize the data. Most previous studies on forecasting model construction have relied...

This study proposes a novel dynamic hybrid model for corporate operating performance forecasting that has been widely acknowledged to be the key trigger of financial troubles. Different from previous studies on measurement merely focus quantitative ratios, we take balanced score cards (BSC) contains and qualitative metrics into consideration further incorporated it with Malmquist data envelopment analysis (Malmquist DEA) handle multiple-inputs multiple-outputs ratios as well capture...

This study introduces a fusion mechanism by incorporating risk metric with two-level data envelopment analysis (two-level DEA) for describing corporate's operation status and then constructs hybrid model that combines rough set theory artificial fish swarm algorithm (RSAFSA) fuzzy support vector machine (FSVM) in order to forecast corporate operating performance. The introduced mechanism, supported real-life cases, can assist both public private market participants who must allocate their...

Under the ravages of COVID-19, global supply chains have encountered unprecedented disruptions. Past experiences cannot fully explain situations nor provide any suitable responses to these fatal shocks on chain management (SCM), especially in todays’ highly intertwined/globalized business environment. This research thus revisits and rechecks crucial components for SCM during such special periods, basic essence covers numerous perspectives that can be categorized into a multiple criteria...

The complex problem of risk factors has greatly increased globally due to the quick ever-changing digital era. development suitable techniques for facilitating performance management in financial service domain is thus an urgent task, especially today’s highly turbulent business environment. such involves many like classical multiple criteria decision-making (MCDM) problem, but too surrounding users will confuse them and lead improper judgments. To deal with this critical study proposes a...

This study introduces a dynamic decision architecture that involves three steps for corporate performance forecasting as such bad has been widely recognized the main trigger financial crisis. Step-1: evaluation and integration; Step-2: model construction; Step-3: knowledge generation. First, making trial laboratory (DEMATEL) is incorporated with balanced scorecards (BSC) to discover complicated/intertwined relationships among BSC’s four perspectives. To overcome problem of BSC cannot yield...

It is widely acknowledged that a corporate's profitability decreases dramatically not only threatens both potential and current investors, but also can freeze stock market transactions as well deteriorate the flow of economic resources. However, far too little attention has been paid to thi s issue, which deemed main trigger for financial crisis. To confront this problem, decision support system be built up evaluate operating performance. Thus, study introduces novel architecture forecasting...

The financial media news reports have helped market participants to know about the strength and weakness of corporate future development, they still encounter a new challenge when analyzing businesses, because their velocity, volume, variety, veracity (4V). In comparison with numerical ratios derived from reports, we believe textual information provides much more essential valuable cues pertaining existence difficulties, preparations satisfy some selective accounting principle or estimation...

Due to the radical changes in global economy and internationalization of markets around world, local corporates are encountering much more severe challenges uncertainties than ever before. Hence, how reliably effectively evaluate whether will exhibit substantial troubl es/difficulties near future turns out be an attractive investigative issue. This study introduces a fusion mechanism that gives decision makers comprehensive description on corporate's operation status so as prevent biased...

Abstract As a result of substantial variations in global financial markets, constructing an enterprise risk prewarning mechanism is essential. A vast amount related studies have implemented monetary-related indicators to depict the full spectrum enterprise’s operating performance. Merely considering unable produce in-depth understanding enterprise. To fill this gap, balanced scorecard (BSC), with advantages being able capture both monetary and nonmonetary indicators, was introduced....

SysML uses the internal block diagram (IBD) and activity (AD) to describe structure behavior of a system respectively. Since IBD AD are heterogeneous separate models, they prone inconsistencies between them, often referred as model multiplicity problems. This paper proposes singularity structure-behavior coalescence (SBC) IBD-AD process algebra solve inconsistency AD. In this SBC algebra, both its projected views, so naturally disappears.

This study proposed a novel hybrid mechanism for corporate operating assessment and then establishes fusion architecture that integrates two-level data envelopment analysis (two-level DEA), incremental filter wrapper feature selection technique (IFWFS), fuzzy support vector machine (FSVM) performance forecasting. The DEA is executed to deal with the problem encountered by one-level (i.e., original DEA) further enhances its discriminant ability. Sequentially, IFWFS applied determine most...

This study examines the impact of corporate social responsibility (CSR) news reports on operating performance forecasting using a large database publicly-listed electronics firms in Taiwan. By executing latent topic modelling, we can break down CSR into multiple dimensions and then examine which dimension(s) affects performance. To offer decision-makers with comprehensive, overarching view corporate's operations, data envelopment analysis (DEA), that handle input output variables...

This study introduces an emerging fusion architecture for managers to predict the corporate operating performance that has been widely recognized as a main trigger financial crisis. To make our assessed outcome more accurate, this goes beyond one DEA model and extends multiple models. However, too much information will confuse mislead judgments made by users. overcome problem, of dimensionality reduction techniques, namely locality preserving projection (LPP), was performed. know at utmost...

This work aims to identify highly potential enterprises by analyzing the positions of in supply chain network. Such may not be famous, but they have compete against large companies or multinationals and achieve considerable growth near future. The proposed approach utilizes social computing technique with balanced scorecard measures analyze network based on rationales that strong industrial relationships are influential a great impact their peers. We construct business item conduct an...

Environmental, social and governance (ESG) has experienced extremely proliferation grew by 42% in recent years.The US Forum for Sustainable Responsible Investment 2020 indicated that the ESG-related investments accounts USD 17.1 trillion of total assets under management professional financial institutes.The corporate with superior ESG performance normally higher values.This value enhancement may be achieved alleviating information asymmetry, increasing future profit cash flow, lowering...