Abstract

This study examines the role of gamification elements in engaging suppliers of sharing economy platforms in corporate social responsibility (CSR) activities. We expected that engaging business owners in CSR would improve the brand equity of these platforms by leveraging the business owners’ brand loyalty and brand association. The statistical population of the study is owners of Iranian accommodation who use sharing economy platforms. The size of the sample was 323 accommodation owners. The hypotheses of this study were tested using Smart PLS-3. The study confirmed all the research hypotheses and showed that engaging business owners in social responsibility activities using gamification elements on sharing economy platforms can lead to an increase in the brand equity of the sharing economy platforms. These results will reinforce the synergy between the platforms and their users by making both parties aware of it.

Introduction

The sharing economy (SE) is where customers and business owners (suppliers) are brought together by an online platform. It is a means by which individuals may leverage their assets, such as their cars, their property and, of course, their time so that these assets may be utilized more thoroughly. This increases the efficiency of society as a whole while either increasing the wealth of participating business owners, or increasing their work flexibility, or both (Kuhzady et al., 2021). Advocatesof the SE have often painted a picture of a utopia where business owners will be set free from the shackles of employment while their customers would be able to take advantage of the lower prices (Belk, 2007). Well known examples of SE platforms are Uber in the ride sharing (taxi substitute) field and Airbnb in the accommodation sharing (hotel substitute) field, though there are also imitators of these platforms which have different degrees of market presence in different parts of the world.

However, the vision presented by SE tends to place its emphasis on the freedom of individuals, whether customers or business owners, while ignoring the fact that one of the reasons for the lower costs and prices of the SE compared with traditional businesses is the lack of regulation designed to counteract some negative consequences. Criticisms of the SE approach (Kuhzady et al., 2021) have included negative social and environmental impacts (Ma et al., 2018), limited safety and security (Birinci et al., 2018) and lack of certainty caused by unknown parties (Hossain, 2020) that contradict the vision of SE platforms of being sustainable and socially responsible. Consumers demand social responsibility from SE platforms and therefore business owners must also adopt sustainability and corporate social responsibility (CSR) principles in their businesses (Mi and Coffman, 2019). Consequently, sustaining the SE requires the engagement of all stakeholders where platforms, consumers and business owners are stakeholders in making a sustainable and responsible SE.

Discussion and conclusion

The study examined the role of gamification elements in engaging accommodation owners in CSR activities and enhancing their experience on SE platforms and how it leads to enriching brand equity through mediating effects of accommodation owners’ satisfaction and trust that leads to brand loyalty and brand association.

ads to brand loyalty and brand association. The gamification elements have a significant effect on engaging accommodation owners in CSR activities on SE platforms based on selfdetermination theory. Analysis of the collected data showed that gamification can have a significant and strong effect on engaging accommodation owners in CSR activities on accommodation sharing platforms. This is consistent with previous research on the power of gamification. Researchers have shown that gamification can be used to transfer complex information and promote green behaviour among users (Souza et al., 2020). In this study, it was shown that gamification elements can be used, not only for customers, but also for the accommodation owners and can engage them in behaving sustainably and responsibly. Analysing the collected data indicates a significant effect of gamification elements on the experience of accommodation owners on SE platforms. This also is consistent with previous studies which indicate that gamification can activate hedonic emotions and ultimately enhance the user experience (Hsu and Chen, 2018). It was also concluded that this hedonic experience is not limited to customers but also includes the business owners.

Abstract

Fintech revolutionized the traditional banking business models in emerging countries. The effect of fintech on banks’ operating efficiency and risk-taking behavior is still inconclusive. The study is aimed at exploring the effect of fintech products on banks’ operating efficiency and risk-taking behavior. The study used a quantitative research approach by collecting secondary data from annual reports of 50 commercial banks from emerging countries, namely, China, India, Pakistan, and Bangladesh, for the period 2014 to 2021. The study used panel data for path analysis and structural equation modeling (SEM) to test the theoretical mediation model by using STATA. The results show that the fintech product reduces the bank’s risk-taking behavior by enhancing the bank’s operating efficiency. The path analysis results show that operating efficiency mediates the relationship between fintech products and bank risk-taking behavior in emerging countries. The paper offers useful recommendations for central bank and commercial bank policymakers. The study is also beneficial for commercial banks that use fintech solutions to increase operational effectiveness and reduce risk. The study is the first empirical investigation into the connection between the growth of fintech products, bank operational effectiveness, and risk-taking behavior in developing nations.

Introduction

The global financial industry has been rapidly changing with the advancement of financial technology over the last few years. New emerging technologies such as Internet finance, blockchain, and mobile banking are penetrating, forming the fintech that revolutionized the whole financial industry. It offered lower-cost services with more choices for consumers to buy financial services that shift their financial behavior to digitalization. The rise of financial technology (fintech) has brought about significant changes in the financial industry, including the way banks manage risk. Fintech has introduced new tools and technologies that enable banks to more accurately assess and manage risk, as well as new business models that challenge traditional approaches to risk-taking.

The pace of fintech development in developed and emerging economies countries is different. In developed countries such as the UK, USA, and Europe, fintech extended the financing transaction methods through algorithmic trading, helping the manager to build better compliance systems to manage risk, and it also improves the electronic payment systems for both domestic and cross-border payments [1]. However, in developing countries, fintech adoption has been slow despite having growth and expansion opportunities in the digital economy (Zhang et al., 2020). Fintech has expanded financial services digitally across countries, particularly during the COVID-19 pandemic. During the pandemic, the usage of fintech services and products has increased tremendously as identified in research [2].

Conclusion and Recommendations/Implications of the Study

The evolution of digital technology has changed the world drastically. The COVID-19 pandemic changed the whole business structure. The customers’ increasing demand for fintech products increases the competition in the financial industry. To retain their customers and remain competitive in the industry, traditional banks adopted fintech products. So that they can deliver efficient, accessible, and low-cost financial services to their customers with the help of technology. Fintech has facilitated the banking industry with better user experience and lower costs by using technological advancement.

The primary objective of the study is to explore the relationship between fintech products and bank risk-taking behavior with mediating role of a bank’s operating efficiency using a sample of commercial banks from China, India, Pakistan, and Bangladesh. The empirical evidence shows that the bank’s risk-taking behavior decreases, and bank stability is improved with the development of fintech products. Fintech products improve the bank’s operating efficiency. The effect of fintech products on bank risk-taking is more pronounced in countries such as China and India because they are extensively using fintech products in their operations. Banks are adopting fintech products such as artificial intelligence blockchain, mobile banking, and Internet banking. The results show that the banks adopting fintech products in their initial phase increase the bank risk-taking behavior, and then later on, it decreases the bank risktaking behavior by improving their operating efficiency.

Abstract

Purpose – Recent studies on the securities market’s differential pricing of earnings components indicate that cash flows from operations are valued more highly than extreme total accruals. However, no previous study has examined whether cash flows from operations have a higher valuation than moderate total accruals. Therefore, this study examines the securities market’s differential pricing of cash flows from operations and both moderate and extreme total accruals

Design/methodology/approach – The study’s sample is divided into two sub-samples: a moderate total accruals sub-sample; and an extreme total accruals sub-sample. To evaluate whether cash flows have a higher valuation when compared to total accruals, for the entire sample and for each of the two sub-samples, the study examines the statistical significance of the difference between slope coefficients of cash flows and total accruals for regression of returns on both unexpected cash flows from operations and unexpected total accruals

Findings – Consistent with prior research, results from the entire sample show a differential higher valuation of cash flows when compared to total accruals. Another finding, consistent with recent studies, is that cash flows from operations have a higher valuation when compared to extreme total accruals. However, there is no higher differential valuation of cash flows over moderate total accruals. These findings support the decomposition of earnings into the components of cash flows from operations and total accruals only when total accruals are extreme (rather than moderate).

Practical implications – A possible explanation for these results is that since accruals predict cash flows, total accruals – when moderate (i.e. not extreme) – are priced similarly to cash flows. These results reveal that when total accruals are moderate, earnings are a better proxy for the underlying cash flows (over the entire future horizon, not just the current period) than is cash flows. However, since total accruals are unlikely to persist in a permanent way over the years, these results indicate that the decomposition of earnings into the components of cash flows from operations and total accruals is consistent with the information set used to value equity securities. Therefore, separate disclosure of cash flows is value relevant. In addition, users of financial statements certainly need the cash flows information as an ex-post validation of the prior earnings.

Originality/value – This study’s contribution stems from its determination of the preferred level of disaggregation of earnings components (i.e. operating cash flows and total accruals). This is expected to help investors in their attempt to enhance the outcome of their informed investment and credit decisions.

Introduction

Reported numbers can be considered informative if they assist investors in making more informed decisions. When stock prices change in response to reported numbers, it can be presumed that investors’ valuation, buying, and selling decisions are influenced by reported numbers. It follows that reported numbers inform their decisions. Earnings can be divided into total accruals and cash flows from operations [1]. Earnings components (i.e. operating cash flows and total accruals) can be considered incrementally informative in relation to total earnings if they assist investors in making decisions that are more informed compared to those made when only the total is known. For example, if investors think that current cash flows are more or less informative when compared to total accruals with respect to their ability to predict future cash flows, then they are likely to be interested in learning about these earnings components and not simply total earnings. Identifying the preferred level of disaggregation regarding the elements of earnings can assist investors in making more effective investment and lending decisions. With these considerations in mind, the present study seeks to investigate the differential price of earnings components in the securities market.

Results

5.1 Stock returns and earnings components for the entire sample Table 2 presents the results regarding the relationship between stock returns and earnings components (i.e. cash flows from operations and total accruals) for the entire sample. The sum of the coefficients for the level and change in cash flows (α1þα3) is 1.218 (t 5 6.743), which is significant and positive at the 1% level. The sum of the coefficients for the level and change in total accruals (α2þα4) is 0.699 (t 5 11.311), which is significant and positive at the 1% level. These results suggest that both cash flows from operations and total accruals have incremental information content beyond each other.

Abstract

We investigate an unexplored channel—loss given default (LGD)—through which accounting information can shape the design of debt contracts. Using a sample of defaulted bonds, we find that borrower accounting information available at contract initiation possesses significant power for predicting realized LGD at the subsequent default date. We then use this model to construct an accounting-based measure of expected LGD at the contracting date for a large sample of bond issuances. We find that this measure is positively associated with issuance date interest spread and covenant use, and document that these relations are not artifacts of an association between LGD and probability of default. We then show that accounting-based expected LGD has a stronger association with issuance date spread when the borrower’s underlying accounting is more conservative and when the accounting-based LGD predictors are more persistent. Our results increase our understanding of both the informational role and contracting role of accounting information.

Introduction

Financial reports are an important source of frm-specifc information available to lenders at the contracting date and thus may afect lenders’ behavior in the design of debt contracts. Whereas prior literature focuses on the usefulness of accounting information for probability of default assessment (e.g., Beaver 1966; Altman 1968; Shumway 2001), this study suggests that accounting information may also shape contracts by facilitating lenders’ assessment of loss given default. Loss given default, defned as the percentage loss that lenders experience from $1 of outstanding principal in a case of default, is a critical component of credit risk and debt contracting theories.1 Despite the theoretical importance of loss given default, there is little empirical evidence regarding how accounting information available to lenders at the contracting date is associated with their expectations about loss given default. This study is the frst to provide evidence that accounting information at the contracting date is a useful predictor of realized loss given default and that lenders behave as if they use accounting information about loss given default to design debt contracts.

Conclusion

A substantial body of research focuses on the informativeness of accounting information with respect to probability of default. However, there is very little research concerning the informativeness of accounting information with respect to loss given default, particularly at the contracting date. There exists some ancillary evidence in extant literature regarding the informativeness of accounting data about loss given default at the time of default. However, given the relatively long time between debt issuance and eventual default, this evidence says little about whether accounting information is useful to lenders in assessing expected loss given default at the contracting date—when lenders need information the most.

This study contributes to the literature along several dimensions. First, using a sample of defaulted bonds, we show that accounting measures available to lenders at the contracting date are informative about future loss given default. To the best of our knowledge, this study is the frst to do so. This fnding complements the literature which shows that accounting measures are informative about probability of default and therefore enhances our understanding of the informational role of accounting. Second, we construct an intuitive measure of accounting-based expected loss given default at the time of bond contract initiation, which could be of use in future research. Third, we show that lenders behave as if their accounting-based expectations about loss given default signifcantly afect price and non-price terms of bond contracts. We provide evidence that the association is stronger when the accounting-based predictors are more persistent, consistent with the intuition that accounting information with higher persistence is more reliable for predicting future outcomes. This fnding contributes to the literature on the role of accounting information in debt contracting by showing a specifc channel through which accounting information may be useful in lending decisions. Finally, our results provide important evidence that establishes a direct link between accounting-based LGD estimation and lenders’ demand for fnancial reporting conservatism.

Abstract

     Previous studies on the impact of firm growth on survival have paid little attention to agglomeration externalities. This study theoretically analyses how different agglomeration externalities affect the relationship between growth and survival. Using data from China’s manufacturing start-ups, we confirm a U-shaped relationship between the growth and survival risks of start-ups. Moreover, we find that different agglomeration externalities have heterogeneous moderating effects on this U-shaped relationship. Specifically, specialization and diversification externalities have significantly negative and positive moderating effects, respectively. The positive moderating effect of diversification externalities comes from the moderating effect of related variety externalities, whereas unrelated variety externalities have no significant moderating effect. The robustness test results support the above conclusions and suggest that the moderating effect of specialization externalities is heterogeneous in terms of firms’ resources.

Introduction

     In strategic management, growth is believed to affect not only the success of a firm at a certain stage but also its survival. Regarding growth as a strategic choice and process facilitates a deep understanding of a firm’s early survival process (Gjerløv-Juel and Guenther, 2019, Pe’Er et al., 2016). Many studies have discussed the relationship between growth and firm survival. The literature enriches our understanding of the survival outcomes of growth, but a consistent conclusion has not yet been reached.1 Moreover, existing research on the relationship between growth and survival rarely considers the interactions between growth and external factors.

     Recent studies have emphasized that exploring the underlying mechanism of business failure requires consideration of internal and external factors (Karabag, 2019, Zhang et al., 2019). They argued that, although few studies have explained how the interaction of firms’ external environment and managerial decisions (or strategic actions) contributes to business failure, interaction is not unimportant. Thus, when exploring the drivers of firm failure, we need an integrated framework that includes internal and external factors and considers the interaction of internal and external factors. Therefore, research on the survival outcomes of growth may need to be systematically reexamined to explore the role of the external environment.

Conclusions

     In strategic management, scholars emphasize that firm survival results from the external environment and internal decision-making. In this study, we use China’s manufacturing start-ups from 1999 to 2007 as a research sample to investigate the impact of growth on survival and analyze the moderating effect of different agglomeration externalities on the relationship between growth and survival. A U-shaped relationship exists between growth and survival risk for Chinese manufacturing startups. Given that most observations fall on the left side of the U-shaped curve, the positive effects of growth dominate.

     Different agglomeration externalities have different moderating roles in the relationship between growth and survival. Specialization externalities play a negative moderating role because they provide benefits that are substitutes for growth benefits and reduce the costs of growth. Meanwhile, diversification externalities play a positive moderating role because they push firms to rely on their internal growth benefits to survive and increase growth costs. After decomposing diversification, we find that the moderating effect of related variety externalities follows the same direction as that of diversification externalities, whereas unrelated variety externalities have no significant moderating effects. Therefore, the positive moderating effect of diversification externalities arises from related variety.

Abstract

     Our investigation of 46 conventional and 22 Islamic banks from the Gulf Cooperation Council (GCC) countries during 2008–2021 reveals that sectoral diversification effects on stability are nonlinear and different for the two bank types. While Islamic banks’ stability is worsened only by moderate levels of diversification, conventional banks’ stability is enhanced by high levels and impaired by low levels of diversification. Furthermore, diversification acted as a stabilizer during the global financial crisis but exacerbated the adverse effects of the Covid-19 pandemic. Although regulators usually call for bank diversification, our results imply that it can be a double-edged sword.

Introduction

     Due to dependence on oil and gas revenue and their price plunge caused by the Global Financial Crisis (GFC) in 2008, the governments of the Gulf Cooperation Council (GCC) countries started introducing various policies aiming at developing diversified real and financial sectors.1 While oil and gas production still represents over 40% of the GDP in GCC countries, with the exception of Bahrain and UAE, (Esam, 2021) shows that there has been significant diversification away from hydrocarbon revenue since 2010 in all GCC countries, particularly in Saudi Arabia, UAE and Bahrain. Given the low development of capital markets and non-bank financial institutions in these countries, banks play a pivotal role in assisting the execution of these national diversification policies by providing financing to support investments in the existing and ‘new’ sectors. The proponents of diversification in banking would see this as an opportunity for banks to spread their loans and financing2 across different sectors and thus reduce bank default, liquidity, and bankruptcy risks (Diamond, 1984; Demsetz and Strahan, 1997; Rose and Hudgins, 2006), vulnerability to economic downturns and financial crises (Tabak et al., 2011; Doumpos et al., 2016), and become safer and more stable (Saunders and Walter, 2012). On the contrary, the opponents of diversification would argue that banks are better off by focusing on a single sector or a few sectors as that allows them to leverage their screening and monitoring knowledge and expertise in these sectors and thus reduce the unnecessary complexity, agency problems, overhead expenses (Klein and Saidenberg, 2010), earnings volatility (DeYoung and Roland, 2001), and write-downs and write-offs (Jahn et al., 2013) that usually come with diversification.

Discussion and conclusion

     Against the backdrop of the GCC countries’ ongoing economic diversification policies and banks being the primary financiers of the projects brought about by these policies, we investigate (i) if and how diversification of loans and financing across economic sectors impacts the stability of GCC banks, (ii) if the effects are the same on conventional and Islamic banks, and (iii) if diversification helps banks navigate smoothly through economic downturns such as the 2008 global financial crisis and the ongoing Covid-19 pandemic.

     anks navigate smoothly through economic downturns such as the 2008 global financial crisis and the ongoing Covid-19 pandemic. Analyzing a unique panel dataset of 46 conventional and 22 Islamic banks, we find that there is no one-strategy-fits-all even within these seemingly similar countries. Diversification effects on bank stability are nonlinear and different for Islamic and conventional banks. While Islamic banks’ stability worsens at moderate levels of diversification, conventional banks’ stability thrives at high levels and erodes at low levels of diversification. Given that the diversification measure is an inverse measure of concentration, this means that a high concentration of loans on one or a few economic sectors also benefits conventional banks. Lastly, we observe a temporal dimension of our results which suggests that diversification supported bank stability against the destabilizing effects of the global financial crisis but amplified the adverse effects of the Covid-19 pandemic.

Abstract

We analyze stock market participation in 19 European countries, providing a composite view of the interplay and relative importance of established participation drivers. We jointly control for nearly all relevant drivers found in prior studies, which tend to introduce one novel variable at a time and often omit risk-aversion. Excellent full model predictive power decomposes into institutional (country) fixed effects (about 30% of total), traditional individual-level variables (50%), and more recently identified behavioral variables (20%). We sketch a hierarchical framework where factors’ effects vary by agents’ proneness to participate. We also challenge and complement existing interpretations given to sociability, IQ, trust, and life experiences.

Introduction

Limited stock market participation has been the quintessential topic in the emerging field of household finance.1 Differences in stockholding propensity across countries, and between people of comparable wealth, show that country factors related to economic or cultural institutions are important. On the individual level, wealth, income, and education are highly influential. Besides these traditional factors, more recent studies have uncovered an interesting set of behavioral factors that explain stock market participation. What is missing, however, is a composite view of the interplay and relative importance of the various drivers of participation.

In this paper, we take a novel, big-picture approach. Whereas the literature has tended to focus on testing the effect of a single new factor after controlling for traditional ones, we combine an extensive set of these variables in one model and explore the relative contribution of three types of factors – institutional, traditional, and new behavioral ones. We jointly estimate the effects of all variables while including a directly queried financial risk aversion measure known to predict actual financial risk-taking well (Dohmen et al., 2011; Halko et al., 2012; Guiso et al., 2018; Laudenbach et al., 2020). Then, based on the contribution of individual explanatory variables in various regulatory environments and subsamples of varying sophistication, we sketch a hierarchical model that describes the likely importance of each factor in different contexts.

Conclusion

The stock market participation literature has progressed steadily over the past few decades, but in step-by-step fashion, usually by adding one novel explanatory variable at a time. We take a consolidating approach by examining the roles of institutional, traditional, and behavioral factors, independently and jointly. We use data from SHARE, which comprehensively cover traditional drivers of participation, including risk aversion, and nearly all of the behavioral drivers from the recent stock market participation literature. We take full advantage of the data, exploiting cross-country variation in regulatory quality and varying levels of wealth and education across individuals.

Institutions clearly matter. Of the explanatory power, institutional factors captured by country fixed effects account for about a third. The traditional individual-level variables capture about 50%, and less than a fifth of the variation is explained by the new behavioral variables. We show that the effects of traditional variables and new behavioral variables change across levels of regulatory quality and across levels of wealth and education. In environments where participation rates are higher, such as high regulatory quality countries and among the wealthy and highly educated, variables reflecting values and attitudes have larger effects. In environments with lower levels of participation these variables have smaller or even non-significant effects. To complete our comprehensive approach, we also take a look at individual behavioral drivers and document complementing and contrasting results with previous literature.

Based partly on our results, and partly on prior research, we suggest a hierarchical model of participation drivers. In this model, similar in spirit to Maslow’s (1943) hierarchy of needs, the low-level factors, such as wealth, have to be on a sufficient level before high-level, e.g., psychological, factors can come into play. Further progress in explaining non-participation, particularly among the well-off, would likely benefit from a focus in the high end of the model.

Abstract

The Internet of Things (IoT) is becoming pervasive and with each new installation of IoT platforms new and legacy brokers have to be exploited. New internal brokers are those under the control of the platform, while legacy external brokers are those in place managed by third parties. The solution proposed addressed problems of (a) interoperability to reduce set up time to cope with unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning both front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capability features of the data warehouse. Interoperability aspects have been addressed by introducing our concepts and a reasoner into an IoT Directory tool to manage Internal and External brokers, automate device discovery and registration from both standard and customized data models. Despite the managed complexity, a broker-based solution turned out to provide high performance. To this end, a specific assessment and architecture tuning have been performed and reported in the paper to give evidence and validation. The proposed integrated IoT Directory has been developed in the context of the Herit-Data Project, and it is currently used in the whole Snap4City network of 18 tenants and billions of data. Snap4City is an open-source IoT platform for Smart Cities and Industry 4.0, which is an official FIWARE platform and solution, EOSC service and libs of Node-RED.

Introduction

The Internet of Things (IoT) defined a paradigm for the computation and communication amongst things, which is becoming every day more and more pervasive and adopted in many different domains [1,2]. It is partially due to the worldwide intense deployment campaign about Low-Power Wide Area Network technologies [3], as well as to many approaches and protocols for communications amongst devices (e.g., Message Queue Telemetry Transport or MQTT, Next Generation Service Interfaces or NGSI, Advanced Message Queuing Protocol or AMQP, Constrained Application Protocol or COAP). The approach is also covering the cloud and fog infrastructures [4,5]. Thus, IoT network infrastructures are becoming every day more complex to be managed due to the networks’ structure and existence of several protocols, formats, and concepts [1,6]. Hence, the complexity is growing in terms of data management, not only for huge amount of data but also for interoperability and abstraction levels needed to data managing. Relevant aspects to be considered are security and privacy [7] on specific data models and entities. To increase the complexity, there is a range of different owners and managers who may control different parts of such IoT networks [8].

In this context, the concept of Gateway is relevant for any segments of IoT networks connecting, as well as for the Web of Things, WoT [9]. Gateways may be integrated with one or more Brokers to send/receive data to/from Devices/entities. The Gateways and Brokers are typically compliant with a single protocol and may be managed by third parties with respect to data management platform. In some cases, they are provided as public services for several interested customers in the same area (for example: Proximus for LoraWAN services [10]). A Gateway may abstract from the IoT Broker level managing multiple brokers for multiple organizations/tenants (which can be regarded as customers of Gateway services to manage several Devices), via some API and/or Web user interface. Typical IoT Brokers can only manage one organization, and thus are single tenant, meaning they broker messages using topic/entity concepts (which can be regarded as the key for subscription on that specific device/entity) without any internal partition of services, but as a sort of family of devices and subscriptions. Some IoT Brokers can be multi-tenant, such as the FIWARE Orion Broker [11,12], which provides support for partitioning the served devices/entities/topics in groups, and each of them may have a dedicated service/path for a specific scope (or a specific customer). Furthermore, devices of different tenants could exist physically in different places (even having identical identifiers, IDs), and the subscription to the broker’s tenant may imply receiving all messages/services in the partition in push. That is feasible only if the subscriber knows the service/path identifier and, in the event of access control, the subscriber has the grant to access the broker’s services. Different IoT Devices connected to the same broker adopt the same protocol, may use different data structures/models and have the same semantic information.

Conclusions

The proliferation of IoT devices, brokers, networks, data models, operators and tenants, makes the harmonization and management of IoT Platform a hard goal. This paper offers an analysis and a comparison amongst relevant existing platforms, and it points out the basic requirements to achieve such aims. These identified requirements are in most cases not addressed by main platforms which prefer to stay on their own end-to-end solutions with limited interoperability and capacity of exploiting legacy IoT networks in place, in terms of performance. The proposed solution addressed problems of (a) interoperability by reducing set up time to efficiently detect and learn how to process unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning the front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capabilities features of data warehouse.

As to interoperability, the main identified and solved problems are those related to a large variety of Data Models coming from non-controllable External Brokers. The issue has been solved by designing and implementing a harvester and reasoner that is capable to automatically recognize/understand and map the new data models/types into those already known by Knowledge Base. This approach, together with the definition of a comprehensive meta model and dictionary, has allowed to speed up the process more than 800 times. The harvesting and comprehension process can be periodically performed to keep the platform updated with any newly defined data models by third party brokers. Furthermore, the process is helped by Km4City ontology and Data Dictionary to recognize the new data types and models according to the semantic domain.

Abstract

This study examined whether foreign investment flow and overconfidence can influence stock price movement among the publicly listed companies in Indonesia. Subsequently, this study determined whether there was any significant difference in the influence of foreign investment flow and overconfidence on stock price movement before and after the COVID-19 lockdown in Indonesia. This study focused on the manufacturing companies listed on the Indonesian Stock Exchange for the 2020 period of which the data were taken in a period of 10 days before and 10 days after the implementation of the COVID-19 lockdown in Indonesia. Using content analysis on secondary data, this study showed that there was a significant difference between the stock prices before and after the COVID-19 lockdown. However, this study showed that foreign investment flow and overconfidence were not the main factors influencing stock price movement before and after the lockdown. The findings indicate that there are other factors that contribute to stock price movement in Indonesia. This study contributes to the existing literature on whether foreign investment flow and overconfidence influence stock price movement in a pandemic world.

Introduction

The COVID-19 pandemic has had an effect not only on the health sector but also on the economic sector all over the world (Ghani et al. 2022). Indonesia is not an exception to this situation. The Central Statistics Agency (BPS) revealed that Indonesia’s economic development in the first quarter of 2020 witnessed a growth of 2.97%, which is a significant change from the 5.02% growth that was recorded in 2019. In Indonesia, the pandemic had a negative impact on the capital market including a change in trading hours on the Indonesian Stock Exchange (BEI) (Kusnandar and Bintari 2020) which, consequently, affected stock price movement. On 8 April 2020, the Combined Stock Price Index (IHSG), which shows the aggregate change in the share price of companies listed on the BEI, showed a decrease in stock prices by around 1.34% at 4704.58. However, upon the government’s announcement of imposing the COVID-19 lockdown, trading hours resumed, causing a steady movement in the stock prices. The existence of unstable stock price movement results exposed investors to increasing risk and uncertainty (Kartika 2008).

Results

5.1. Analyses before COVID-19 Lockdown

Table 3 presents the results of the normality test before the COVID-19 lockdown. The Asymp. Sig. (two-tailed) result was 0.346, which is greater than 0.05. Therefore, it can be concluded that the data were normally distributed, or, in other words, the data passed the normality test.

Table 4 presents the results of the normality test after the COVID-19 lockdown. The table shows the value of Asymp. Sig (two-tailed) to be 0.349, which is greater than 0.05. Therefore, it can be concluded that the data were normally distributed, or, in other words, the data passed the normality test.

Abstract

This paper builds a network econometric model capable of analysing the impact of inflation on systemic risk. Its main contribution is the identification of a robust inverse relationship which reverses when controlling monetary policy. This reveals that the former effect is due to monetary policy reactions to inflation. It is further analysed whether this effect comes from overindebtness as in a Minsky moment. There is no evidence supporting it, which suggests that mechanisms other than excess credit underlie such a relationship. The results presented in this paper are of particular importance for understanding monetary policy reactions to current inflationary cycles.

Introduction

Analogously to many other macro-financial linkages, the effects of inflation on systemic risk are, to a large extent, still unknown. This is the result of a disconnection between the interplay of the economy and financial markets which has dominated macroeconomic research in recent decades. However, the financial crisis of 2007–2009 made clear that there is a constant interaction between the economic system and financial markets (Diebold and Yılmaz, 2015, Abbas et al., 2019, Balcilar and Bekun, 2020, Cotter et al., 2020, Silva et al., 2017, Festić et al., 2011, Aliyu, 2012), highlighting the need to consider additional contagion channels rather than the traditional interbank market (Silva et al., 2018). Thus, many of the macro-financial variables depend the other dimension, potentially in a non-linear way, as it has been theoretically argued (Bernanke et al., 1999, Gertler and Kiyotaki, 2010, Mendoza, 2010, Brunnermeier and Sannikov, 2014) and empirically estimated (Giglio et al., 2016).

In particular, the effects of inflation on systemic risk are of special importance nowadays. After more than 20 years of relatively low inflation (see red line Fig. 1, quantified on the right axis), the study of the inflation-financial stability binomial have not been of upmost importance. Thus, some studies have analysed the impact of inflation on the performance of the financial sector (Boyd et al., 2001), financial development (Festić et al., 2011), and many have analysed the relationship between inflation and public debt (Bhattarai et al., 2014, Krause and Moyen, 2016, Cherif and Hasanov, 2018). However, the recent inflationary shock has caused “seismic waves” for the stability of the financial system, as contractive monetary policy stances have revealed, among other concerns, overexposures to interest rate risks by financial institutions. Therefore, discounting monetary policy, there may exist a relationship between inflation and systemic risk which could make controlling inflation a major concern not only for the correct functioning of the economy, but also for ensuring the stability of the financial system. As shown in Fig. 1, this correlation between inflation and systemic risk connectedness may exist a priori.

Conclusions

This paper has provided some inferences about the effects of inflation on systemic risk in a financial network of twelve countries. It has been found that, after controlling the monetary policy reactions to inflation, inflation increases systemic risk. Furthermore, in the time span considered (2000–2022), inflation increases more systemic risk than interest rates. This provides partial equilibrium evidence in favour of aggressive monetary policy interventions to preserve financial stability and not only to ensure the correct functioning of the economy during inflationary shocks. Indeed, if inflation increases more systemic risk than interest rates, there exists an incentive for the central bank to increase interest rates in presence of rising inflation, since the effect of the latter outweights the negative effect of the bank rate hike for financial stability.

It has been further tested whether the channel through which inflation increases systemic risk is excessive lending during economic booms as in a Minsky moment. However, evidence has not been found which reveals that mechanisms other than excess credit are behind the relationship. All the results presented in this paper are robust to several variable selections and econometric specifications, and extend to inflation expectations as well. Further research can be directed towards increasing the understanding of the relationship between inflation and systemic risk with monetary policy, since a substantial part of it appears to be happening through interest rates.

Abstract

A growing body of literature scrutinizes the harmful consequences of capital flight to offshore financial destinations. While financial integration is a well-known facilitator of capital flight, we shed light on an under-appreciated determinant—the availability of an IMF bailout. Expanding on previous literature analyzing moral hazard in the context of IMF programs, we introduce a socially even more destructive mechanism that we label the ‘crash for cash’ effect. We argue that by drawing on the IMF, elites can benefit from accumulating excessive debt to extract rents and hide these safely in offshore financial destinations while steering their countries into financial disaster. To test this mechanism, we show that elite wealth in offshore bank accounts has a first-order impact on a captured government’s willingness to draw on a lender of last resort. From a policy perspective, our analysis underscores the importance of closing financial loopholes to mitigate the devastating socio-economic effects of sophisticated financial engineering in a financially integrated global economy.

Introduction

Capital flight is a key obstacle to sustainable development. While policymakers often point the finger at financial investors, in many cases, well-connected local elites drive capital flight into offshore financial destinations. These elites plunder the wealth of their countries and expatriate assets into safe havens (Jayachandran and Kremer, 2006, Garcia-Bernardo et al., 2017, Andersen et al., 2020).1 Depriving a country of investible capital can lead to a loss of tax revenues and rising inequality, to the effect that elite capital flight ultimately undermines macroeconomic stability (Alesina and Tabellini, 1989, Ndikumana et al., 2014, Frantz, 2018): notwithstanding its ethical status, such behavior undermines the quality of governance, furthering endemic corruption and crony business practices that amplify financial vulnerabilities (Cerra et al., 2008, Meierrieks and Schneider, 2021).

Previous literature analyzing the determinants of elite capital flight identifies dysfunctional governance frameworks that provide a fertile breeding ground for criminal activities such as embezzlement, trade misinvoicing, and tax evasion (for a review, see Cooley et al. (2018)). Weak institutions facilitate capital flight because they allow wealthy elites to move embezzled funds abroad without punishment (Collier et al., 2001, Ndikumana and Boyce, 2003, Le and Rishi, 2006).

Conclusion

The IMF plays a vital role in supporting countries during times of economic hardship, earning it a reputation as “a global payday loan company for countries who have got into trouble and can’t meet their financial commitments — the difference being that instead of charging sky-high interest rates, it demands radical economic reforms”.33

Researchers have analyzed the circumstances under which the IMF decides to intervene and the conditions it imposes in exchange for financial relief (e.g., Reinsberg et al., 2019). We analyze the role of international capital flight and its impact on IMF involvement and program design. We argue that the ability to draw on the IMF creates perverse economic incentives so that a country’s elites can privatize economic gains by moving funds into offshore financial destinations before the arrival of the Fund. Although the Fund possesses numerous instruments to address economic crises, it does not have any means to seize elite wealth in offshore financial destinations, so the costs of elite capital flight are passed onto the population at large.

Abstract

     We study the inter-temporally optimal innovation strategies of incumbent manufacturing firms that compete in an established market and can extend their product line through product innovation. Firms invest in production capacity and R&D knowledge stock, where the R&D knowledge stock and the current R&D investment determine the hazard rate of innovation. Our findings show that the firms’ optimal R&D strategies are driven by a subtle interplay between the relative positions of their R&D knowledge stocks and their current relative positions on the established market. First, we find that under symmetric investment costs the knowledge leader should spend more on R&D than the knowledge laggard only if it has a substantially smaller market share on the established market. If the knowledge leader’s market share is sufficiently large, its optimal investment in R&D is so small that its innovation rate is lower than the knowledge laggard’s. Second, optimal investment in R&D knowledge is negatively affected by the opponent’s production capacity on the established market if the competitor has not innovated yet. However, we find that this effect is reversed after the competitor has successfully introduced the new product on the submarket. Third, the manufacturing firm with higher costs of adjusting production capacity for the established product has a higher incentive to engage in product innovation and might even achieve a higher total discounted profit than its more efficient competitor.

Introduction

     A considerable fraction of product innovations in related submarkets is accomplished by established incumbents (e.g. Buensdorf, 2016, Chandy, Tellis, 2000, Franco, Sarkar, Agarwal, Echambadi, 2009, King, Tucci, 2002, Sood, Tellis, 2011). This observation raises the question how an incumbent’s optimal strategy in an R&D race depends on its strength on its established market. To illustrate, in 2010 when Apple and Samsung introduced Tablet PCs and thus created a new submarket that coexisted with the established market of portable computers, they had relatively small market shares on the Laptop market (3.4% and 2.8% respectively) compared to Hewlett Packard and Dell (18% and 12% respectively). Interestingly, HP and Dell entered the Tablet market much later in 2013.1 In the market for smartphones, Nokia, as the clear market leader in the early 2000s (market share 2005: 32.5%), introduced its first touchscreen phone in 2011, while its initially smaller competitor Samsung (market share 2005: 12.7%) introduced its first smartphone with a touchscreen in 2008. As a result, Samsung achieved a higher market share in 2012 and also exhibited strongly positive dynamics of profit in the smartphone market compared to Nokia.

Conclusions

     In real-world markets, action-reaction or increasing dominance patterns of innovation can be observed. Under action-reaction, the smaller incumbent manufacturing firm in the established market becomes the innovation leader in the new market. Under increasing dominance, the dominant incumbent manufacturing firm in the established market also dominates the new market. In this paper, we develop a stochastic duopoly framework in order to highlight some of the drivers that endogenously lead to one of these patterns of innovation in equilibrium. In particular, we study the factors that determine the incentives of incumbent firms to invest in the development of a new product which extends their product range. Our dynamic setting particularly emphasizes the interplay between the firms’ relative positions in terms of their R&D knowledge stocks and their relative strengths on the market for the established product. We explicitly take into account that the adjustment of production capacities as well as the build-up of R&D knowledge are costly and take time.

Abstract

     This paper empirically examines the effect of inefficient corporate investment on digital transformation, using Chinese listed companies from 2007 to 2019 as a sample, and finds that inefficient investment is not conducive to improving digitalization. We find that the greater the financing pressure on a company, the worse the digital transformation, and financing constraints exacerbate this negative effect. Among state-owned, private and highly digitalized companies, the negative impact of inefficient investment on digital transformation intensifies as the pressure of financing constraints increase. To combat inefficient investment, enterprises should optimize their investment structure, reduce their financing constraints, and improve their risk prevention mechanisms.

Introduction

     The global economy and society are in a critical stage of digital transformation, and the supporting and leading role of the digital economy for industrial development is becoming increasingly important (Wen and Zhong, 2020). As we enter a “new normal” period, where growth rates gradually decrease, the development of the digital economy becomes an important tool for China on its journey to being a high quality, innovative country. With the in-depth implementation of China’s manufacturing sector, network infrastructure and big data strategy, the development of the digital economy has gained momentum, with the overall scale expanding from 18.6 trillion yuan in 2015 to 39.2 trillion yuan in 2022, and the proportion of GDP attributed to the digital economy increasing from 27% to 38.6%, thereby becoming a key driver of stable economic growth. However, these impressive achievements have also raised some concerns. Corporate digital transformation requires investment and high technical standards, leaving some who refuse to transform, as well as those who are ready (Liu et al., 2021). Therefore, understanding the potential value of digital transformation is an issue of great concern to both academia research and policy makers.

Conclusions and recommendations

     This paper takes Chinese listed companies from 2007 to 2019 as a research sample, and empirically tests the impact of investment efficiency on corporate digital development, and the mediating effect of financing constraints, and the conclusions obtained are as follows:

1 The results show that inefficient investment is detrimental to digitalization; there is a positive relationship between investment efficiency and digitalization, and the higher the financing pressure on a company, the more unfavorable the digital transformation, and financing constraints exacerbates this negative effect.

2 The financing constraint has a more significantly negative moderating effect on the relationship between inefficient investment and digitization levels for state-owned firms, private firms, and firms with higher digitization levels.

3 Companies can alleviate financing pressure to a certain extent through inefficient investment, but it is still fundamentally detrimental to their digital transformation.