Abstract

This study presents a novel financial performance forecasting method that combines the threshold technique with Artificial Neural Networks (ANN). It applies the threshold regression method to identify the factors within the board of directors that influence the financial performance of traditional industries in Taiwan. The findings indicate that the ANN method effectively predicts financial performance by using relevant board structure data. Furthermore, the empirical results suggest that boards with more members demonstrate increased profitability. Additionally, a more significant presence of board members with accounting expertise contributes to more consistent profits. In contrast, an increased presence of members with financial expertise has a more pronounced impact on profitability.

Introduction

Traditional industries, including sectors such as metal machinery, the chemical industry, and subsistence industries, have played pivotal roles in Taiwan’s economic development, trade, and industrial evolution over the years. However, in recent years we have witnessed the emergence of economic powerhouses and the rapid progress of regional economic and trade partnerships like ASEAN, resulting in significant changes to the global economic and trade landscape. As a result, these industries are now operating within a new and highly competitive environment. In this era of rapid transformation, these industries must identify the essential factors that will enable them to maintain and enhance their positions on the international stage.

Investors seek to achieve multiple objectives through the election of a company’s board of directors. They aim to enhance corporate governance, safeguard the rights and interests of shareholders, and anticipate that the board will contribute expertise to improve the decision-making prowess of the board itself. Ultimately, this is expected to enhance the company’s overall performance. Consequently, whether the board of directors can positively impact corporate performance has remained a significant research focus in management and academia.

While many studies have explored the relationship between the board of directors’ characteristics and company performance, a notable need exists for more in-depth articles examining the professional backgrounds of the board members and CEOs and how their leadership qualities influence financial performance. This gap in research underscores the need for a more comprehensive understanding of the intricate dynamics between leadership, professional expertise, and corporate financial outcomes.

Conclusions

The research results show that, for companies in traditional industries that are listed on the Taiwanese stock market, the composition of the board of directors impacts the business’s financial performance.

Boards with more members may have a greater capacity for overseeing corporate governance. A greater representation of board members with accounting expertise tends to lead to more consistent corporate profits, whereas an increased presence of members with financial expertise results in more pronounced profit fluctuations. Additionally, in the case of companies with lower profits, managers may face pressure from loan contracts or receive limited attention from investors, potentially leading to heightened practices related to profit management. Managers may aim to maximize their benefits. At this time, the return on assets is high, and the managers obtain the expected benefits. Thus, to restrain the profit management behavior of managers, enterprises need to have a broader view and have specific judgments and analyses in each enterprise to build organizational structure and procedures. The operation of the board of directors is more effective because of the industry’s characteristics, the enterprise’s size, the capital structure, and the performance of the enterprise. Finally, this study used deep learning and big data techniques to build an Artificial Neural Network (ANN) model that specializes in predicting the ROA of companies based on most factors related to board structure, with a prediction accuracy of over 78%.

Abstract

Competing effectively in the contemporary marketing landscape is becoming increasing challenging. Equally increasing therefore is the pertinence for organisations to be customer oriented. Academic discourse emphasises the need for more customer-oriented approach. Inspired by gaps in the literature, this study explores the contingency factors and performance implications of customer accounting in the Kuwaiti financial services industry. A questionnaire was used to collect data, and data analysis was based on 115 responses from management accountants of participating firms. This study reports critical insights that enhance the no one-size fits all notion of contingency foundation. For organisations in the industrial and geographical setting covered in this study, the insights from this study offer relevant cues for optimising customer accounting operationalisation and maximising the organisational performance impact. The limitations of this study have been acknowledged and critical directions for further knowledge development flagged.

Introduction

For many decades, scholars have emphasised the importance of management accounting in organisational dynamics (e.g. [1,2,3,4]. Theoretically, it is contended that if organisations endorse and effectively implement management accounting practices, they would achieve improved performance. A plausible rationale for that argument is that management accounting plays the critical enabling role of providing management with relevant information to enhance managerial decision-making for overall organisational performance (e.g. [5,6,7]. Given this importance, there is increasing research interest on management accounting practices (e.g.[4, 6, 8,9,10].

Despite that increase, there is still much room for empirical research towards enhancing the understanding of this topic. (e.g. [6, 11,12,13,14]). Bearing in mind that successful managerial decisions improve overall organisational profitability [15, 16] and also that the extent to which the overall organisational profitability is improved hinges on strategic alignment (e.g. [17,18,19]), the focus on management accounting has evolved much for over 25-years now, with scholars emphasising more the strategic component (strategic management accounting) (SMA). Within this focus, scholars advocate for a management accounting approach that gives due attention to the need for accounting for strategic positioning [19,20,21]. Elaborated by Langfield-Smith [9], SMA advocates contend that accounting should be strategically tailored towards achieving a more market-oriented focus.

Discussion and conclusion

Theoretical implications
This study contributes to the understanding of customer accounting practices usage, contingency factors, and organisational performance impact (e.g. [6, 24, 25, 51]). With regard to customer accounting practices usage, this study contributes in the way of reinforcing prior research that underlines the importance for a customer-oriented accounting approach in management accounting (e.g. [6, 10, 24, 25]). The results from this study show that Kuwaiti FSOs are embracing customer accounting practices as a way of staying customer oriented.

Secondly, this current study contributes to the literature on the contingency factors of customer accounting practices usage (e.g. [6, 24, 25, 48, 51]). The evidence from this study offers supports and contrasts to past literature, an outcome that thus add support to the contextual intricacies that surround contingency features. This study argues that competition intensity would aid the adoption of customer accounting practices, evidence that reinforces Foster and Gupta [48] but contrasts Ojra [6] who found no support in the Palestinian context. Furthermore, this current study supports and contrasts Guilding and McManus [51] who suggest a support as well as contrast for the notion that high competition intensity would lead to high customer accounting practices usage.

Abstract

     This paper responds to the lack of empirical evidence on how enterprise risk management (ERM) and the financial performance of small and medium-sized enterprises (SMEs) are related. Structural equation modeling is used to explore new mediators in the relationship between ERM and SME financial performance. The results show that organizational culture (mission dimension) and strategic risk management performance are full and positive mediators between ERM and financial performance. These research results highlight the fact that the implementation of ERM in an enterprise does not by itself generate the expected effects without the existence of a mature organizational culture and the monitoring of strategic risk management performance. These findings are particularly relevant for SMEs with “pretend ERM” that lacks the strategic and operational components. ERM also helps to transform the negative effect of foreign capital in SME equity on financial performance into a positive effect.

Introduction

     Increasing levels of uncertainty call for proactive risk management in all organizations. The parallel crises triggered by the COVID-19 pandemic (Chakraborty and Maity 2020) and the military conflict in Ukraine have impacted most industries and businesses, unlike the Great Recession of the late 2000s, which primarily affected the financial sector (Gertler and Gilchrist 2018). Systematic risk has long been underestimated in advanced economies (Pagach and Wieczorek-Kosmala 2020). In such a situation, an intuitive assessment of risk outcomes, as often performed by smaller enterprises, is not enough (Grondys et al. 2021). Companies face new challenges and find it harder to maintain their profitability and competitiveness. Therefore, holistic enterprise risk management (ERM) is becoming increasingly important in small and medium-sized enterprises (SMEs).

     Nonfinancial SMEs are mostly unregulated. Thus, there is little pressure to implement a comprehensive risk management system. Nevertheless, in recent years, SMEs have started implementing formal risk management processes to increase their competitiveness (Wirahadi and Pasaribu 2022). ERM improves the quality of the information about enterprise risk profiles. The adoption of ERM reduces systematic risk. The purpose of ERM is to reduce the probability of losses and, therefore, reduce the need to borrow external resources, which positively impacts the expected cost of capital (Berry-Stölzle and Xu 2018).

Conclusion and implications

     Regarding the theoretical implications, this study reveals new mediators between ERM and the subjective financial performance of SMEs. The PLS-SEM method is suitable for analyzing complex relationships and testing causal relationships. Exploring indirect pathways can reveal consequential effects and help managers and owners understand various relationships. Complicated ERM indices (e.g., Gordon et al. 2009) are not suitable for the nonfinancial sector because the input variables for calculating such indices are difficult or impossible to obtain. The model works with the direct and indirect effects of ERM implementation. The indirect effects show the crucial role of organizational culture (mission dimension) and evaluations of strategic risk management performance in the relationship between ERM and the subjective financial performance of SMEs.

     From the management perspective, it is essential to establish functional and integrated processes for ERM implementation. ERM must be integrated with the organizational culture and the performance monitoring systems in the SME. Managers and owners should emphasize the functional implementation of ERM, not just a pretend ERM (Syrová and Špička 2022a) that lacks all the elements of an ERM approach. The ERM system must not be a “facade without the substance” that does not contribute to better planning and decision-making processes (Dvorski Lacković et al. 2022).

Abstract

     While the strategic use of social media (SM) for enhancing firm performance has attracted much attention, little is known about it through the lens of business-to-business (B2B) small and medium-sized enterprises (SMEs). Building on the market-driven view and the dynamic capabilities view of competitive strategy, we examine SM use in a framework of market-sensing and customer-linking capabilities that influence firm performance. Our research model posits that market orientation stimulates SM use to enhance market-sensing capability thereby facilitating two customer-linking capabilities, namely customer relationship management and brand management, which collectively contribute to greater marketing performance and financial performance. Our research model is empirically tested using a survey of 143 UK B2B SMEs. The findings broadly support our theorization in which the strategic use of SM, an essential part of market-sensing capability, enhances customer-linking capabilities. Interestingly, although SM use influences brand management capability, its suggested influences on both customer relationship management capability and marketing performance occur only through the mediation of brand management capability. Both customer-linking capabilities positively influence marketing performance and in turn financial performance. Our findings provide novel conceptual and empirical advancement of how market-centric B2B SMEs strategically use SM to enhance their market-sensing and in turn customer-linking capabilities, and hence firm performance.

Introduction

     With the increased digitalization of marketing activities, marketing professionals are increasingly adopting social media (SM) as a strategic tool to effectively engage with customers and broader stakeholders (e.g. Chaker, Nowlin, Pivonka, Itani, and Agnihotri, 2022; Pardo, Pagani, and Savinien, 2022); develop new products (Du, Yalcinkaya, and Bstieler, 2016); increase brand awareness (Deng, Wang, Rod, and Ji, 2021); co-create value (Itani, Krush, Agnihotri, and Trainor, 2020); and improve firm performance (Cheng, Liu, Qi, and Wan, 2021). More and more researchers suggest that firms must have an SM presence since the strategic use of SM is increasingly seen to enhance firm competitiveness (e.g. Cartwright, Liu, and Raddats, 2021; Tiwary, Kumar, Sarraf, Kumar, and Rana, 2021).

     The likely gains from SM technologies are particularly evident in business markets where customers are more informed and less dependent on interactions with salespeople (Ancillai, Terho, Cardinali, and Pascucci, 2019). For example, leading large firms such as Adobe, IBM, and Maersk Line are increasingly using digital channels and SM to facilitate effective dialogue with customers (Ancillai et al., 2019). The growing evidence suggests that SM can be strategically used to facilitate an effective dialogue with customers (Kovac, 2016), create brand awareness, or differentiate the focal brand from the competition (e.g. Deng et al., 2021; Swani, Brown, and Mudambi, 2020), provide customer care, and/or improve firm performance, among others (e.g. Salo, 2017; Tiwary et al., 2021).

Conclusion

     Overall, our study examined the much-advocated and under-investigated strategic use of SM for enhanced B2B marketing strategy. We opted to focus on the B2B SME context where it argued that due to the resource-constrained operating environment experienced by SMEs, the use of SM platforms will be particularly beneficial due to easiness of implementation, low-cost accessibility, and cost-efficiency. We promised our inquiry on the dynamic capabilities view and Day’s (1994) seminal framework of capabilities in market-driven firms and theorized that the strategic use of SM provides a meaningful link between market orientation and CLC. Overall, our research model captures how the strategic use of SM strengthens MSC to effectively seize market opportunities through (re)developing two key CLC that drive enhanced marketing performance and in turn financial performance. Overall, the strategic use of SM remains a fertile ground for further inquiry in B2B marketing strategy context.

Abstract

     This study examines the association between firms’ ESG reputational risk and financial performance under the EU regulatory policy changes and the COVID-19 period. Analyzing a panel of 1,816 European listed firms during the period 2007–2021, we document evidence that firms with lower ESG reputational risk have reduced information asymmetry, are less financial constrained and perform better. To establish causality, we design a quasi-natural experiment focusing on the 2014/95/EU directive of non-financial disclosing and the COVID-19 exogenous shock. Our findings are robust to several estimation techniques that address endogeneity, self-selection, and model sensitivity.

Introduction

     In recent years, the concept of environmental, social, and governance (ESG) has attracted considerable interest (Stroebel and Wurgler, 2021; Krueger et al., 2020), however, its potential impact on firm financial performance is ex ante unclear. Today, modern companies follow ESG strategies not only to boost their performance but also to reflect their values and contribute to a better world (Ferrell et al., 2016; Starks et al., 2017, Dyck et al., 2019, Hartzmark and Sussman, 2019). Moreover, there is an escalated demand from consumers for high ESG standards (Godfrey, 2005) and increased pressure on regulators and policy makers to address environmental pollution, workplace diversity and firms’ transparency (Yan et al., 2019). In this direction, the COVID-19 pandemic crisis has amplified the sensitivity to social issues, human capital, health, safety, and responsible practices more than ever before.

     According to Reuters,1 ESG-focused funds received a record $649 billion in investments in 2021, making over 10% of all assets globally. These assets have done better than market benchmarks. ESG due diligence involves managing both a financial opportunity as well as risk. For instance, Volkswagen’s participation in the Dow Jones Sustainability Index was confirmed just a few days before the US public learned about the 2015 US emission crisis.

Conclusion

     This study examines the impact of ESG reputational risk on European firms’ financial performance. Using different econometric techniques, we document a causal negative and statistically significant relationship between ESG reputational risk and financial performance. Our findings also have economic significance. In line with asymmetric information theory, we argue that in the presence of ESG reputational risk, there is increased information asymmetry between stakeholders and managers, which leads to adverse selection and increased cost of equity and financial underperformance. In addition, the market may interpret ESG reputational exposure as a negative signal. We draw insights from the literature’s distinction between “good” and “bad” firms considering their environmental, social, and governance performance. Consistent with agency costs theory (Friedman, 1998, Jensen, 2001, Benabou and Tirole, 2010, Cheng et al., 2013, Kim and Lyon, 2015, Kruger, 2015, Siano et al., 2017), we document that ESG-responsible firms align better with managers’ and stakeholders’ interests and decrease managerial myopic decisions (Eccles et al., 2014, Albuquerque et al., 2019); therefore, these firms have comparatively better financial performance and market value.

     We further explore the relationship between ESG informational risk and firms’ financial performance under the EU regulatory policy changes arising from the 2014/95/EU directive and the COVID-19 global pandemic. We show that ESG reputational risk, both in the presence of lower informational asymmetries (2014/95/EU directive) as well as high informational asymmetries (COVID-19 global pandemic), negatively predicts firms’ financial performance. This evidence supports our argument that lower ESG reputational risk increases financial performance by transmitting important information to investors and signaling firms’ true protentional dynamics, thus reducing ex ante uncertainty.

Abstract

     We analyze the likelihood of financial statement manipulation among 19 listed manufacturing and trading firms on the Ghana Stock Exchange for the period 2008 to 2017. We use the Beneish model to group the firms into those likely to engage in financial statement manipulation and those not likely to be involved in financial statement manipulation. Generally, the results show that majority of the firms are likely to be involved in financial statement manipulation. Also, we find that profitability, liquidity, financial leverage, change of audit firm, and the overall economic condition (Z-score) are firm-level factors that predict the likelihood of financial statement manipulation among listed manufacturing and trading firms in Ghana. Given the high number of manufacturing and trading firms likely to engage in financial statement manipulation, there is the need for the managers of the Ghana Stock Exchange to subject future financial reports of these firms to rigorous scrutiny to safeguard the interest of their stakeholders.

Introduction

     Three objectives drive this study. First, the study seeks to detect the likelihood of financial statement manipulation1 among listed firms in Ghana using the Beneish (1999) model. Second, it examines whether financial ratios characteristics differ among firms that are likely to engage in financial statement manipulation and those not likely to manipulate their financial statements. Third, it determines the financial ratios2 that predict the likelihood of financial statement fraud.

     The fundamental purpose of corporate financial reporting is to provide the actual state of affairs of an entity to its stakeholders. The rationale is that users of financial reports found their economic decisions on information contained in such reports (Kanapickienė & Grundienė, 2015). It is for this reason that financial statement fraud is considered a serious legal and ethical issue in accounting practice. In this study, financial statement fraud is defined as any act of omission or misstatement deliberately done or committed by a firm in its financial reporting that distorts the entity’s real state of affairs. This definition, to a considerable extent, dovetails into that of Apostolou, Hassell, and Webber (2000), who define corporate financial fraud as the “intentional misrepresentation of amounts or disclosures in the financial statements” (p.181).

Conclusion

     The research seeks to detect financial statement manipulation among 19 listed manufacturing and trading firms in Ghana using the Beneish model and financial ratios. The study covers 2008 to 2017 fiscal years. We use a probit regression technique to predict the probability of a listed manufacturing and trading firm engaging in corporate financial fraud. The results demonstrate that the majority of listed manufacturing and trading firms are likely to engage in financial statement manipulation. The study, therefore, concludes that financial statement manipulation may be prevalent among listed manufacturing and trading firms in Ghana. Again, sales to fixed assets ratio (SAL/FA), total debt to total assets ratio (TD/TA), earnings before interest and tax to sales ratio (EBIT/ SAL), gross profit to sales ratio (GP/SAL), cost of sales to sales ratio (COS/SAL), working capital to total assets (WC/TA), current assets to current liabilities (CA/CL) and Z-score are the financial ratios that differ significantly between firms likely to engage in corporate financial statement fraud and those not likely to do so. A probit regression analysis has shown that profitability, overall financial condition, liquidity ratios as well as a change of their external auditors predict the likelihood of listed manufacturing and trading firms getting involved in financial statement manipulation.

Abstract

     Financial fraud has extremely damaged the sustainable growth of financial markets as a serious problem worldwide. Nevertheless, it is fairly challenging to identify frauds with highly imbalanced dataset because ratio of non-fraud companies is very high compared to fraudulent ones. Intelligent financial statement fraud detection systems have therefore been developed to support decision-making for the stakeholders. However, most of current approaches only considered the quantitative part of the financial statement ratios while there has been less usage of the textual information for classifying, especially those related comments in Chinese. As such, this paper aims to develop an enhanced system for detecting financial fraud using a state-of-the-art deep learning models based on combination of numerical features that derived from financial statement and textual data in managerial comments of 5130 Chinese listed companies’ annual reports. First, we construct financial index system including both financial and non-financial indices that previous researches usually excluded. Then the textual features in MD&A section of Chinese listed company’s annual reports are extracted using word vector. After that, powerful deep learning models are employed and their performances are compared with numeric data, textual data and combination of them, respectively. The empirical results show great performance improvement of the proposed deep learning methods against traditional machine learning methods, and LSTM, GRU approaches work with testing samples in correct classification rates of 94.98% and 94.62%, indicating that the extracted textual features of MD&A section exhibit promising classification results and substantially reinforce financial fraud detection.

Introduction

     With the boom of the securities market in last decades, more and more companies raise capital and expand the operation scale through listing, especially in fast growing counties like China. Accompanied by financial market development, fraudulent financial reports have cast rapidly, and have caused dramatic losses to shareholders with negative impacts on capital markets [1], [2]. The Enron scandal in the U.S. in 2001 and the global financial crisis spanning 2008–2009 have severely damaged the world economy [3]. In China, the number of criminals involved with fraudulent activities in 2019 is more than 961 with a value of more than $8 billion [4]. Although there are minor variations in its definition, a financial statement fraud is referred as ‘‘deliberate fraud committed by management that injures investors and creditors through misleading financial statements’’ [2]. Generally speaking, the main reason for fraud is due to the inaccurate reports of CPAs and auditors. In addition, companies with rapid growth may exceed the monitoring process ability to provide appropriate supervision. According to report issued in 2020, only a limited number of fraud cases were identified by internal and external auditors with rates of 14% and 5%, respectively [5]. As a result, effective detecting financial fraud has always been an important but rather challenging task for accounting and auditing professionals given that the economic and social consequences can be massive [5], [6].

Conclusion and Future Research Directions

     While financial fraud has a negative impact on economic and social development, it also causes huge losses to different stakeholders. However, detecting financial statement fraud is fairly challenging using traditional approaches due to companies’ stratagem. Our main purpose of conducting this research is building models with high classification performance and deriving classification framework which can be used to detect the frauds with textual and numeric data in Chinese listed companies’ annual reports. As the most advanced information processing technology, deep learning has made great achievements in many applications. In this way, this paper gives a framework for how this technique can be used in financial statement detection with Chinese companies’ annual reports. Besides numerical data in financial statements, we analyze the ability of textual data attached to annual reports in financial statement fraud prediction and highlight the importance of textual analytics for detecting fraud with financial documents. Also, the results have shown that the deep learning models achieved considerable improvements in AUC compared to the earlier studies on the financial fraud detection. Furthermore, the textual information of the MD&A section of annual reports extracted through deep learning has the ability to improve the accuracy of financial statement fraud model detection, particularly in the highly unbalanced case of fraud detection.

Abstract

     The cost of public construction projects is a central topic in project management. However, studies have primarily focused on cost at the project level, not on cost management at the portfolio level. In this paper, we take the perspective of a government agency, conducting a strategic initiative to increase cost-efficiency in their portfolio of construction projects. We use an action research approach to investigate the dynamics of the initiative and the implementation of resulting actions to achieve lasting change towards cost-efficiency. Co-creating actions for cost-efficiency together with the project teams was important for the success of the strategic initiative. For successful implementation, alignment of the objectives of the initiative with organizational strategy, and knowledge transfer between projects is central. This study expands the project management literature regarding strategic cost management of portfolios of construction projects and provides practical guidance for organizations.

Introduction

     Any project-based organization (PBO) that wants to achieve lasting change needs to take action. For a lasting effect, the changes need to be institutionalized, which implies learning from temporary actions to permanent practices. A wide specter of challenges that occur in such settings, has been studied in the literature (e.g. Saunders et al., 2008; Stensaker et al., 2008; Kunisch et al., 2019; De Melo et al., 2020). However, these studies tend to focus more on theory than on what happens in reality. This study responds to the need for more practice-based research in the field that explores the reality of strategic enactment through a project portfolio (Clegg et al., 2018) and uncovers linkages between practices, organizational learning and change (Brunet, 2019). Additionally, Klessova et al. (2020) ask for more empirical studies to understand the processes that influence knowledge integration in the context of innovation projects.

     In this paper, we report on an empirical study concerning how a public organization conducted an initiative to lower the overall cost of their construction projects. Project cost is a complex issue and influenced by many factors. However, it is relevant to all types of projects as it can be a decisive factor in whether to invest at all, when choosing between project alternatives, or in a client’s decision of which organization will conduct a project.

Conclusions

     In the previous chapter, we have discussed the results of this study and answered the research questions. In the following paragraphs, we will present the study’s contribution to both theory and practice and discuss the validity of the study as well as suggestions for further research.

6.1. The study’s contribution to project management knowledge

     This study contributes to the project management literature by providing a rich empirical account of a strategic cost-efficiency initiative in a project-based organization, which has not been previously focused on in the literature. Applying an organizational sociology perspective to the initiative shifts the focus from individual projects to the portfolio as a unit of analysis. The observed dynamics of the strategic initiative align with previous research on the necessity of sensemaking through action in the implementation of change activities (Stensaker et al., 2008). It also adds the dimension of a project-based organization to the findings by Willems et al. (2020) with respect to how the autonomy of strategic initiatives influences the implementation of results in the permanent organization.

Abstract

     This article helps resolve the current unsatisfying and inclusive studies covering the efficiency of stock markets in developing countries. Previous studies have used limited data and partial statistical tests. We use a large, unique data set, across 12 countries, and a comprehensive set of traditional and recent statistical methods as well as powerful multiple-break unit root and spectral analysis tests, many of which have never been used to evaluate the efficient market hypothesis (EMH) in emerging markets. Our results confirm the rejection of the EMH for emerging markets. Our findings have important implications for investors and policy makers, suggesting the possibility for excess profits in these markets.

Introduction

     The idea of efficient markets has been a central topic in financial theory since Eugene Fama introduced it in 1970. The efficient market hypothesis (EMH) states that financial asset prices entirely reflect all available information, making it impossible for investors to beat the market. The theory has received significant support from academics: Shiller (1981), Carhart (1997), Lettau and Van Nieuwerburgh (2008), Fama and French (2010), Busse, Goyal, and Wahal (2010), and Bertone, Paeglis and Ravi (2015). The award of the Nobel Prize in Economics to Richard Thaler in 2017 has helped reignite this debate. Thaler, one of the founders of “behavioral finance” has put the notion of EMH in doubt and provided scientific explanations for the existence of irrational market behaviors. The empirical evidence is mixed and the research community is “torn” between the EMH and behavioral finance camps (Verheyden, Moor, and Bossche 2015).

     After extensive research of the EMH in developed markets, a widespread but not complete consensus exists that developed markets tend toward efficiency although there are periods of informational inefficiency and periods of speculative bubbles (behavioral finance), (French and Roll (1986), De Long and Becht (1992), Carhart (1997), Fama and French (2010), Busse, Goyal, and Wahal (2010), Bertone, Paeglis, and Ravi (2015).

Empirical Results

     Table 1 presents the summary statistics of the data. As found in many prior studies, all the series in the sample are not normally distributed on their associated J-B statistics. The stock markets in Taiwan, Thailand, and Mexico developed earlier, with starting dates in July 1998. Columbia, Malaysia, Indonesia, and Hong Kong began much later, beginning July 2005. The return series are quite similar, with the exception of Hong Kong, during the study period. We also examine the correlation matrix (results not shown) and observe that these return series are positively (and statistically significant) related, similar to those found in developed markets in several prior studies. The non-normality is significant because the very high kurtosis numbers indicate the likelihood of extreme returns. Also, the skewness numbers help reinforce that volatility with positive values indicates some extreme gains and many small losses, and vice versa for negative values.

     Table 2 displays the variance ratio test results. First, as revealed in the table, the null hypothesis of random walk is decidedly rejected in all countries in the sample at the 1% significance levels for periods 2 through 16. Second, the Wright (2000) tests, not shown (as discussed), yield nearly identical results for all countries. These results are similar to several of those reported in some of the reviewed articles, using older data sets.

Abstract

     In a financially globalized world, managing long-term interest rates through short-term interest rates can be difficult. In this paper, we examine whether net capital inflows contribute to weakening the link between short- and long-term interest rates. We find that more financially open economies or those with more developed financial markets tend to have a greater negative relationship between net capital inflows and short- to long-term interest rate pass-through. We also examine whether macroprudential policies can affect the extent of interest rate pass-through and find that broad-based capital macroprudential tools are effective in retaining control of interest rate pass-through.

Introduction

     Recently, many researchers have argued that fnancial globalization has made domestic fnancial markets more vulnerable to developments in the major economies, namely the United States, the European Union, and lately China. Rey (2013) argues that in the fnancially globalized world, countries are vulnerable to the “global fnancial cycle” of capital fows, asset prices, and credit growth. In such an environment, non-major economies are subject to the center countries’ monetary policy unless the former decides to curtail capital mobility

      Figure  1 makes it clear that the volume of capital fows to emerging market economies (EMGs)2 tends to rise when risk appetite, measured by the reversed VIX index, is higher3 . When “risk is on,” investors’ risk appetite would rise and capital would fow to where the yields are higher, which was the case for EMGs when industrialized countries (IDCs) implemented extremely low interest rate policies in the late 2000s through the mid-2010s. When “risk is of” or when the interest rates are expected to rise in IDCs, capital would leave EMGs for IDC’s markets. Thus, capital fows to EMGs only passively react to the conditions of the major economies.

Concluding Remarks

     It has been increasingly argued that fnancial globalization has been playing a bigger role in determining domestic asset prices and interest rates. In such an environment, even with greater monetary autonomy, monetary authorities may not be able to keep controls of fnancial markets and the real economy as Rey (2013) argues. In fact, in recent years, the correlation of long-term interest rates between EMGs, especially those in East Asia, and the United States has been rising while the correlation of short-term rates does not show such a trend. In other words, Rey’s (2013) view of global fnancial cycles afecting domestic monetary policy – in which policymakers face a dilemma between monetary autonomy and free capital mobility – may be applicable to long-term interest rates, though not to the short-term interest rates.

     We examine whether receiving net capital infows can contribute to weakening the link between the short- and long-term interest rates, i.e., the interest rate passthrough. Our estimation results suggest that a country receiving more net capital infows tends to have a weaker interest rate pass-through. When we instrument net capital infows with its potential determinants to control for potential endogeneity, we fnd that both the magnitude and the statistical signifcance of the estimate for net capital infows increase.

Abstract

     Financial data, such as financial statements, contain valuable and critical information that may assist stakeholders and investors in optimizing their capital to maximize overall economic growth. Since there are many variables in financial statements, it is crucial to determine the causal relationships, that is, the directional influence between them in a structural way, as well as to understand the associated accounting mechanisms. However, the analysis of variable-to-variable relationships in financial information using standard correlation functions is not sufficient to unveil directionality. Here, we use the volatility constrained correlation (VC correlation) method to predict the directional relationship between two arbitrary variables. We apply the VC correlation method to five significant financial information variables (revenue, net income, operating income, own capital, and market capitalization) of 2321 firms listed on the Tokyo Stock Exchange over 28 years from 1990 to 2018. This study identifies which accounting variables are influential and which are susceptible. Our findings show that operating income is the most influential variable while market capitalization and revenue are the most susceptible variables. Surprisingly, the results differ from the existing intuitive understanding suggested by widely used investment strategy indicators, the price–earnings ratio and the price-to-book ratio, which report that net income and own capital are the most influential variables affecting market capitalization. This analysis may assist managers, stakeholders, and investors to improve financial management performance and optimize firms’ financial strategies in future operations.

Introduction

     The advent of information technology has made it possible to store and classify a large amount of financial data in real time on an unprecedented scale [1]. Financial information can be represented by a vast variety of data types. However, one of the most abundant types of data is multivariate time-series data, in which correlations among different assets are often used to perform risk management analysis, determine investment strategies, and improve financial management. The correlation structure in financial markets has been investigated in many studies at different scales. Preis et al

     analyzed 72 years of daily closing prices of the 30 stocks of the Dow Jones Industrial Average and found that the average correlation among the stocks is linearly scaled with market stress at various time scales [2]. Laloux et al. applied random matrix theory to understand the statistical structure of the correlation matrix of price changes and showed that there is a significant agreement between theoretical predictions and real data related to the density of eigenvalues [3]. This study raises serious questions about Markowitz’s naive use of empirical correlation matrices for portfolio risk management. Plerou et al. also applied random matrix theory to analyze the cross-correlation matrix of price changes of the largest 1000 US stocks [4]. Their findings showed that randomness cannot explain the universal and non-universal properties that enable the identification of cross-correlations between stocks. Jiang and Zheng uncovered the positive and negative subsector structures of Chinese, US, and global stock markets by applying a random matrix theory analysis and taking into account the sign of the components in the eigenvectors of the cross-correlation matrix [5]. Cross-correlations between volume change and price change of financial indexes were studied by [6]. Long-range magnitude cross-correlations in real-world data from various fields, such as finance, have also been studied intensively, using time-lag random matrix theory [7]. The integration of random matrix theory and network methods was also used to unveil correlation and network properties of 20 financial indexes [8]. The importance and novelty of physical methods applied to the study of financial cross-correlation analysis have been highlighted by Kwapien and Drozdz in their extensive review [9]. In particular, the application of random matrix theory to financial multivariate time series data deserved special attention. In this regard, several works have extended and further applied this statistical mechanics approach to the field of finance, namely [10–15].

Conclusion

     Previous studies of correlation coefficients in finance data have found out about the correlation between two variables but not their direction [2,4–8]. However, we were able to capture the directionality between variables in financial statement data that cannot be captured by ordinary correlation coefficients.

     In this study, the VC correlation approach unveiled the directionality between five major accounting variables, which is difficult to obtain using standard correlation methods. Our data-driven computations yielded new insights on major accounting variables, which can be translated into novel recommendations for investment strategies. We summarize our findings as follows.

     First, from the directionality network, we observed that operating income is the origin of influence on the other four accounting variables (net income, own capital, market capitalization, and revenue). Market capitalization and revenue are the most susceptible accounting variables. Second and more importantly, although market participants often focus on net income and own capitalization to evaluate the share price for investment strategy, operating income may be a better accounting variable on which to focus. Third, the influence order of revenue, operating income, and net income differs from the order of accounting calculation of income statements.

Abstract

     How entrepreneurial orientation facilitates the identification of new opportunities in newly established ventures in emerging economies remains largely unexplored. Approaching entrepreneurial orientation as a second order latent construct, we examined the mediating role of opportunity recognition on new venture performance. Using a survey data from 316 SMEs, the results of the analysis in SmartPLS highlights that entrepreneurial orientation indirectly contributes to the performance of new ventures, where the relationship is partially mediated by opportunity recognition. The findings show that firms with high entrepreneurial orientation can identify and exploit new opportunities as well as enjoy superior performance.

Introduction

     Many emerging economies are confronted with immense challenges such as uncertain markets (Czakon et al. 2020; Yu et al. 2020), globalization (Fatima 2017), new market systems (Alvarez et al. 2015) and intense competition (Chari and Banalieva 2015). As compared to developed markets, new ventures suffer from a higher failure ratio due to institutional challenges. For instance, Wang and Chen (2010) argue that in China, more than 70% of newly established ventures fail in the first year. Another study by Parnell et al. (2015) reports 67% failure ratio of Chinese ventures in the first year while 85% in the first 10 years. Anwar and Ali Shah (2020) report that more than 50% of new ventures in Pakistan do not survive in the long run. These institutional challenges impinge on the growth of small and medium enterprises (SMEs) largely due to the liability of newness and smallness, which limits their ability to adapt rapidly to changing business conditions (Yu et al. 2020). Consequently, the ability of these firms to exploit new opportunities in order to survive the competition is impeded (Zhou and Li 2010; Chen et al. 2020). Thus, bringing to the fore the issue of performance and survival of newly established SMEs in emerging economies (Anwar and Ali Shah 2020; Yu et al. 2020; Guo et al. 2019a).

Conclusion

     Our research examined and tested predictions about the mediating role of opportunity recognition between EO and new venture performance in emerging markets. The study also examined the effect of opportunity recognition on venture performance. Even though we found empirical support for the derived hypotheses, this line of inquiry also opens an opportunity for theory building regarding which dimension of EO is more appropriate in opportunity recognition concerning newly born enterprises in emerging market settings.

Abstract

     Although the management of mergers and acquisitions (M&As) and of projects are connected in practice, they remain disjoined in academia. In this paper, we conceptually bridge the literature on projects and M&As to discuss the transitory nature of organisations by mobilising the concepts of project, programme, and portfolio as alternative modes of organising M&As. As a project, the managerial effort in M&A focuses on completion on time and budget. As a programme, M&As are managed as complex processes of convergence between organisations. As a portfolio, M&A management is part of the ongoing integration efforts within organisations that have grown via M&As. Our contribution to project studies is to position projects, programmes, and portfolios as modes of organising, hence, not as phenomena but as managerial choices used to shape strategic change initiatives, such as M&As. We conclude with implications beyond project studies, thereby drafting a project-based theory of the firm.

Introduction

     Project, programme, and portfolio are established vehicles for managing strategic change (Pellegrinelli, 1997; Geraldi & Söderlund, 2012; Martinsuo & Hoverfält, 2018). Initially, the terms project, programme, and portfolio were used interchangeably, causing confusion and debate about their differences, similarities (Pellegrinelli et al., 2011), and practical implementation (Pellegrinelli et al., 2007). This confusion has been followed by conceptual discussions both in the academic (Maylor, Brady, Cooke-Davies, & Hodgson, 2006; Lycett et al., 2004; Artto et al., 2009) and practitioner literature (PMI, 2017; OGC, 2011), which eventually led to a clear distinction between these three modes of organising project-based work. This has also encouraged the correct classification of a certain phenomenon as a project, programme, or portfolio, and managing it accordingly (Lycett et al., 2004; Maylor, Brady, Cooke-Davies, & Hodgson, 2006).

Discussion: contributions, limitations, and research avenues

     We have offered a conceptualisation of projects, programmes, and portfolios not as a type of work to be conducted, but as ideal typical modes of organising. Accordantly, we argue that a manager could choose to manage the same M&A initiative as a project, a programme, or a portfolio, therefore organising the ensuing activities accordingly, resulting in the strategic initiative being shaped into a project, a programme or a portfolio by managing it as such. Therefore, project, programme, and portfolio become a managerial choice, with implications for the acquisition and the involved organisations in the long term.

     Following Zahra and Newey’s (2009) modes of theorising at the intersection of disciplines, our work offers four contributions. The first two are contributions to the connected research fields. First, to project studies, we propose an alternative perspective of projects, programmes, and portfolios as modes of organising. Second, to M&As, we offer an alternative view of M&A management as an organisation in its own right. Third, our bridge offers possibilities for a theoretical contribution to organisation studies in general, namely the contours of a project-based theory of the firm. Our final contribution is our illustration of theorising at the intersection between research fields. The next sections discuss each of these contributions, boundary conditions, and implications. We conclude with a call for more inter-disciplinarity in organisation and management studies.