Supplier change, market competition and enterprise innovation

PurposeThe purpose of this paper is to study enterprise innovation in the perspective of external supplier relationship. On this purpose, this paper examines the impact of supplier change on enterprise innovation with the moderating role of market competition.Design/methodology/approachUsing 2012–2020 empirical data of Chinese listed manufacturing enterprises, this paper investigates the relationship among supplier change, market competition and enterprise innovation through a two-way interaction model.FindingsThe results show that supplier change has a negative impact on enterprise innovation. And market competition intensifies the negative relationship between supplier change and enterprise innovation. Additional analyses indicate that the main effect and the moderating effect are more significant when the enterprise is non-state-owned or has lower ownership concentration.Originality/valueThis paper studies enterprise innovation from the perspective of external stakeholders. It focuses on supplier relationship in a dynamic variation view, instead of the traditional static ones. Moreover, this paper explores the contingency effect of market competition and gives practical implications for managers to adjust innovation strategy flexibly.

Risk transmission between equity market of China and its trading partners: new evidence from various financial crises

PurposeThe authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).Design/methodology/approachThe authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.FindingsAccording to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.Originality/valueThe authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

Sustainable Enterprise Development in the Manufacturing Sector: Flexible Employment and Innovation in China

Since the COVID-19 outbreak, the scope and market size of flexible employment in sustainable enterprise development have significantly increased worldwide, yet academic literature offer little information about the outcomes and moderators of flexible employment in China. The paper advances current knowledge and empirically addresses this gap by examining the effects of flexible employment on enterprise innovation input and output, with information technology capability and labor regulation as unexplored moderators. Based on data from 1179 manufacturing enterprises in China, this paper uses the OLS method to conduct empirical tests. The results show that (1) flexible employment has positively contributed to sustainable enterprise development by facilitating innovation inputs and outputs;(2) superior enterprise information technology capabilities and strict labor regulations were significant moderating factors in this relationship. The findings provide credible evidence for enterprises to pursue flexible employment as an inexhaustible impetus for sustainable economic and enterprise development.

Novel Method for Estimating Time-Varying COVID-19 Transmission Rate

The transmission rate is an important indicator for characterizing a virus and estimating the risk of its outbreak in a certain area, but it is hard to measure. COVID-19, for instance, has greatly affected the world for more than 3 years since early 2020, but scholars have not yet found an effective method to obtain its timely transmission rate due to the fact that the value of COVID-19 transmission rate is not constant but dynamic, always changing over time and places. Therefore, in order to estimate the timely dynamic transmission rate of COVID-19, we performed the following: first, we utilized a rolling time series to construct a time-varying transmission rate model and, based on the model, managed to obtain the dynamic value of COVID-19 transmission rate in mainland China;second, to verify the result, we used the obtained COVID-19 transmission rate as the explanatory variable to conduct empirical research on the impact of the COVID-19 pandemic on China's stock markets. Eventually, the result revealed that the COVID-19 transmission rate had a significant negative impact on China's stock markets, which, to some extent, confirms the validity of the used measurement method in this paper. Notably, the model constructed in this paper, combined with local conditions, can not only be used to estimate the COVID-19 transmission rate in mainland China but also in other affected countries or regions and would be applicable to calculate the transmission rate of other pathogens, not limited to COVID-19, which coincidently fills the gaps in the research. Furthermore, the research based on this model might play a part in regulating anti-pandemic governmental policies and could also help investors and stakeholders to make decisions in a pandemic setting.

Sellers' inflation, profits and conflict: why can large firms hike prices in an emergency?

The dominant view of inflation holds that it is macroeconomic in origin and must always be tackled with macroeconomic tightening. In contrast, we argue that the US COVID-19 inflation is predominantly a sellers' inflation that derives from microeconomic origins, namely the ability of firms with market power to hike prices. Such firms are price makers, but they only engage in price hikes if they expect their competitors to do the same. This requires an implicit agreement which can be coordinated by sector-wide cost shocks and supply bot-tlenecks. We review the long-standing literature on price-setting in concentrated markets and survey earnings calls and compile firm-level data to derive a three-stage heuristic of the inflationary process: (1) Rising prices in systemically significant upstream sectors due to commodity market dynamics or bottlenecks create windfall profits and provide an impulse for further price hikes. (2) To protect profit margins from rising costs, downstream sectors propagate, or in cases of temporary monopolies due to bottlenecks, amplify price pressures. (3) Labor responds by trying to fend off real wage declines in the conflict stage. We argue that such sellers' inflation generates a general price rise which may be transitory, but can also lead to self-sustaining inflationary spirals under certain conditions. Policy should aim to contain price hikes at the impulse stage to prevent inflation from the onset.

Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study

We study the behavior of an economic platform (e.g., Amazon, Uber Eats, Instacart) under shocks, such as COVID-19 lockdowns, and the effect of different regulation considerations. To this end, we develop a multi-agent simulation environment of a platform economy in a multi-period setting where shocks may occur and disrupt the economy. Buyers and sellers are heterogeneous and modeled as economically-motivated agents, choosing whether or not to pay fees to access the platform. We use deep reinforcement learning to model the fee-setting and matching behavior of the platform, and consider two major types of regulation frameworks: (1) taxation policies and (2) platform fee restrictions. We offer a number of simulated experiments that cover different market settings and shed light on regulatory tradeoffs. Our results show that while many interventions are ineffective with a sophisticated platform actor, we identify a particular kind of regulation - fixing fees to the optimal, no-shock fees while still allowing a platform to choose how to match buyers and sellers - as holding promise for promoting the efficiency and resilience of the economic system. © 2023 ACM.

Impact of Pandemic Outbreak and Targeted Required Reserve Ratio Cut Policy on Stock Return Rate: Evidence from China

This study analyzed the impact of COVID-19 outbreak and targeted required reserve ratio cut policy on stock returns of Chinese listed companies. This paper uses the data of 3,449 A-share listed companies from February 3, 2020 to December 31, 2020 for research, the empirical results showed that stock prices of private enterprises with stronger debt-paying ability and looser financing constraints, and state-owned enterprises with less supply chain credit risks performed better, in the central and western regions, enterprises with stronger solvency and looser financing constraints have better stock price performance during the early stages of pandemic. After the implementation of the targeted RRR cut policy, the stock prices of enterprises with poor solvency, private enterprises, and enterprises in central and western regions with strong financing constraints, state-owned enterprises, and enterprises in eastern region with high credit risks all showed significant reversals, and the stock prices reflected the effect of the targeted RRR cut policy in the short and medium term. Over time, the pandemic has been controlled, and the resumption of work and production has freed most enterprises from financial difficulties. However, due to sporadic outbreaks, large private enterprises and eastern enterprises with strong risk resistance and loose financing constraints enjoy better stock price performance. This study is helpful for enterprises to understand the value of financial flexibility and solvency and provides a reference for enterprises to make financial decisions: how to balance the benefits and costs of solvency. © Tian Wang, Fang Fang and Linhao Zheng, 2023.

Market development strategy and process performance of knowledge-intensive SMEs in the epidemic era: a process-oriented perspective

PurposeThis study analyzes in-depth how knowledge-intensive small and medium-sized enterprises (SMEs) can achieve higher new product development (NPD) process performance in the epidemic era and examine the internal development mechanism of knowledge-intensive SMEs in the process of continuous digital transformation.Design/methodology/approachThis issue is tested with partial least squares on data collected via a survey conducted from November 2021 to February 2022. The sample comprises 487 knowledge-intensive SMEs operating in China.FindingsThe results indicate that one form of cross-functional ambidexterity, market development strategy (MDS), plays an important role in process performance from an inside-out financial perspective and an outside-in customer perspective. Simultaneously, product innovation efficiency (PIE) mediates the relationship between MDS and the above results. Big data analytics capabilities (BDACs) positively regulate the relationship between MDS and PIE.Research limitations/implicationsThe authors do not consider other contingency factors. Future research should introduce influential factors such as leadership and competitive intensity to further distinguish the effects of MDS on NPD process performance.Practical implicationsThe study findings offer suggestions to help knowledge-intensive SME managers better manage their NPD process by making better use of their limited resources in developing countries such as China.Originality/valueThis study is one of only a few to adopt a process-oriented perspective to specifically examine how one form of cross-functional ambidexterity, MDS, impacts knowledge-intensive SME process performance in the epidemic era. This study also extends the theoretical framework of cross-functional ambidexterity to BDAC research.

Studying the impact of COVID-19 on the European Air Transportation Network

The European Air Transportation Network was significantly impacted by the COVID-19 pandemic, resulting in an unprecedented loss of flight connections. Utilizing a combination of graph representation learning and time series analysis, this paper studies the evolution of both the global connectivity as well as the structure of the European Air Transportation Network from January 2020 to December 2022. Specifically, it finds strong differences in recovery rates for flights across six different market segments. In terms of network structure, the study finds that structural roles that are present in the pre-covid network have seen a loss in performance over the course of the pandemic, but have recovered to pre-covid levels. Using regional changes in structural roles, this study identifies Italy as the region with the strongest increase and the United Kingdom as the region with the strongest decrease in structural role, finding substantial differences in recovery rates per market segment. Lastly, this study pays special attention on the effect of the Russia-Ukrainian war on the European Air Transportation Network. © 2023 IEEE.

Competitiveness-the engine that boosts economic growth and revives the economy

Competitiveness is a concept that shows up in all aspects of human life, both at the micro level, in personal, social, and professional life, and at the macro level, linked to organizational and national competitiveness with long-term effects on global competitiveness. In this paper, we aim to address competitiveness in Romania in the current context, before and after the COVID-19 pandemic, highlighting its role in reviving the economy. While until the onset of the pandemic Romania's competitiveness performance was growing, more recently, because of the global health crisis, it dropped a few places, according to the Global Competitiveness Index report. In order to have a clear picture of the degree of competitiveness in Romania, we have presented a series of statistical data for the most relevant macroeconomic indicators for our study for the 2017-2022 timeframe: the global competitiveness index, the minimum wage, labor productivity, the evolution of real labor productivity per employed person, the economic growth rate, the unemployment rate, the inflation rate, the European innovation index, gross domestic expenditure on research and development, export of goods and services as a share of GDP, etc. The methodology used involves the use of quantitative techniques, performing an econometric analysis, and correlating how the most important macroeconomic indicators can influence the degree of competitiveness at both the national and international level. For the post-pandemic timeframe, the analysis switches focus, just as the economic reality did, looking at energy costs and energy use as determinants of competitiveness. Since notions like circular economy and sustainable development correlate being energy-efficient with being competitive, however, at the same time, the high cost of investments necessary for individual businesses and countries to switch from polluting energies to clean energies impedes or at the very least heavily impacts their ability to compete with entities that don't make that same switch, it becomes apparent that the energy market impacts competitiveness metrics. Competitiveness promotes valuable contributors and underpins performance at group and company level, and the effects from the micro level will propagate, with an emission effect, to the entire national economy with obvious implications at the international level, through real growth in macroeconomic indicators, increased labor productivity, increased economic performance (market share, export share, return on capital), raising living standards and economic and social wellbeing (life expectancy index, human development index, poverty rate), education (skills, knowledge, abilities, managerial and marketing skills, corporate culture), competitive potential (innovation, R&D, promotion), and in raising the Global Competitiveness Index by focusing on factors of production, efficiency, and innovation, etc.

Fuzzy-based Telework Capability Evaluation Using AppSheet-based Mobile Application

By the beginning of 2020, the illness had been named as COVID-19, which had spread due to its extreme severity affecting multiple industries and sectors throughout the world. To protect the public's health and safety, the Philippine government has established a number of quarantine regulations and travel restrictions in reaction to the current COVID-19 outbreak. Nonetheless, the ILO predicted that the pandemic would initially disrupt the economy and labor markets, affecting 11 million employees, or around 25% of the workforce in the Philippines. Therefore, the government continues to urge employers of local companies and enterprises to use alternative work plans, such as a WFH - work-from-home operation in accordance with the established policies. In line with the concept of telework, several studies have already been carried out, though some were declared inconclusive and require additional study. Hence, in this research, a mobile application was created to evaluate the employee's telework capability assessment using a Fuzzy-based model which utilizes Google AppSheet, Apps Script, and Sheets. The developed mobile application is able to provide capacity evaluation utilizing the four key input variables, which are also reasonably characterized for potential telecommuting cost evaluation. © 2022 IEEE.

Performance of IPOs During Covid-19 Pandemic and Factors Affecting Investors' Perception

Initial Public Offering (IPO) is a fund-raising tool through which a company gets listed for the first time under SEBI regulation and issues IPOs to raise funds from the public. The shift from a privately-owned to a publicly-owned firm via an IPO is the most significant event in a company's life (Pagano et al., 1998). In an IPO investment, there is limited historical data to analyze and predict the future performance of the company;hence it becomes a risky investment for the investors as they cannot predict how the shares will perform in the future. Most companies that go for an IPO are in the growth or expansion phase so it becomes more difficult to predict their market position and performance in the future, which leads to uncertainty in deriving their future value. Also, most IPOs are of companies going through a transitory growth period, and are therefore subject to additional uncertainty regarding their future value. This study analyzes the performance of the IPOs issued during the Covid-19 pandemic, when the markets across the world faced massive disruptions. The IPOs from various sectors like finance, technology, service, infrastructure, food, pharmaceutical and information technology were considered for the study. The study also analyzes the factors affecting investor perception towards investment in an IPO. The study considered the IPOs issued during the pandemic, and their performance on the listing day was measured by considering issue price, listing price and closing price. It was observed that 90% of the IPOs selected performed well during the listing day and 10% underperformed. It was also found that factors like company brand, company sector, fundamental analysis, company ratings, expert opinion and stock market conditions had a positive impact on the investors' decision to invest in an IPO. The study also revealed that factors like risk factor in primary market, returns on IPO on the listing day and Gray Market Premium have no significant impact on the investors' perception.

Global commodity and equity markets spillovers to Africa during the COVID-19 pandemic

This paper examines the connectedness among 12 African equity markets and the global commodity, developed equity markets, paying particular attention to their evolution during the COVID-19 pandemic's peak period. We find that whilst African equity markets connect weakly to these markets, the levels of connectedness among these markets improved significantly during the pandemic. In addition, the energy market dominates the transmission of shocks in the system with commodity markets. Regarding the system with equity markets, the French and South African equity markets transmit the highest spillover in the full sample and during the pandemic's peak period, respectively. • Examines the connectedness among African equity and the global equity and commodity markets. • Examines the evolution of connectedness among these markets during the COVID-19. • African equity markets are weakly integrated with the global commodity and equity markets • During the COVID-19 peak period, however, the level of integration among these increased significantly. [ FROM AUTHOR] Copyright of Emerging Markets Review is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Impact of the Covid-19 pandemic on unemployment in selected countries and country groups

The economic crisis caused by Covid-19 differs from previous economic crises in several ways. It is a global event that developed unexpectedly and hit the world unprepared, primarily attacking human resources, requiring strong governmental measures. The involvement of the human sphere directly affected people's income and lives through labour market effects. Based on literature and statistical data, this study analyses the evolution of the unemployment data of 11 countries (Australia, Chile, the UK, Israel, Japan, China, Hungary, Germany, Italy, Turkey, and the US) and two country groups (EU-27 and the Organisation for Economic Co-operation and Development - OECD) during the economic crisis. Based on the results, the authors identified three distinct groups of countries with 1. moderate growth, slow consolidation;2. robustious upturn, fast then slow correction, and 3. individual patterns. The study demonstrated how government measures took effect differently from the unemployment perspective. The authors referred to the influence of the inhabitants' collective way of thinking and considered it essential to emphasise the positive impact of vaccines.

Rising Cybercrime on Social Media during Covid pandemic and its Impact on Digital Marketing

Covid pandemic brought a significant change in the way people learn, entertain, interact and conduct business. With people working and socializing remotely, social media usage skyrocketed and provided a fertile ground to cybercriminals to exploit the platforms and its users. This paper will explore the rising trend of cybercrime on social media, including specific types of cybercrime such as phishing scams, impersonation and misinformation. The paper will also discuss about the parties mostly affected by cybercrimes. Additionally, the paper will delve into the impact of increase in cybercrime on digital marketing, including the challenges faced by businesses. Overall the paper aims to provide a comprehensive overview of the current state of cybercrime media during the covid pandemic and how it is impacting the overall society and digital markets all together.

A quantitative framework for health‐care service quality assessment in India

PurposeThe present situation of COVID-19 pandemic has put the health-care systems under tremendous stress and stringent tests for their ability to offer expected quality of health-care services, as it decides the sustainability and growth of health-care service providers. This study aims to deliver a quantitative framework for service quality assessment in the health-care industry by classifying the health-care service quality parameters into four balanced scorecard (BSC) perspectives.Design/methodology/approachTo determine the service quality for the Indian health-care system, decision-making trial and evaluation laboratory and analytical network process are integrated in a fuzzy environment to contemplate the interaction among BSC perspectives and respective performance measures.FindingsThe results indicate "internal processes” perspective assumes the key role within BSC perspectives, while performance measures "nursing staff turnover” and "staff training” play the key roles. The results also signify that "patient satisfaction” is the most vital issue and can be strongly influenced by measures belonging to the "learning and growth” perspective. In "learning and growth” perspective, "staff training” is the most decisive criteria, very highly influencing "patient satisfaction”, highly influencing "profitability,” "change of cost per patient (both in and out patients)” and "outpatient waiting time” while moderately influencing "staff satisfaction,” "bed occupancy” and "nursing staff turnover”. Moreover, "staff training” criteria have a positive influence on "nursing staff turnover.”Originality/valueThe contributions of this study are in two folds in the domain of quantification of service quality for the health-care system. First, it delivers an assessment framework for Indian health-care service quality. Second, it demonstrates an application of the framework for a case situation and validates the proposed framework.

DIBR–DOMBI–FUZZY MAIRCA Model for Strategy Selection in the System of Defense

Strategic management has applications in many areas of social life. One of the basic steps in the process of strategic management is formulating a strategy by choosing the optimal strategy. Improving the process of selecting the optimal strategy with MCDM methods and theories that treat uncertainty well in this process, as well as the application of other and different selection criteria, is the basic idea and goal of this research. The improvement of the process of the aforementioned selection in the defense system was carried out by applying a hybrid model of multicriteria decision-making based on methods defining interrelationships between ranked criteria (DIBR) and multiattributive ideal-real comparative analysis (MAIRCA) modified by triangular fuzzy numbers–"DIBR–DOMBI–Fuzzy MAIRCA model.” The DIBR method was used to determine the weight coefficients of the criteria, while the selection of the optimal strategy, from the set of offered methods, was carried out by the MAIRCA method. This was done in a fuzzy environment with the aim of better treatment of imprecise information and better translation of quantitative data into qualitative data. In the research, an analysis of the model's sensitivity to changes in weight coefficients was performed. Additionally, a comparison of the obtained results with the results obtained using other multicriteria decision-making methods was conducted, which validated the model and confirmed stable results. In the end, it was concluded that the proposed MCDM methodology can be used for choosing a strategy in the defense system, that the results of the MCDM model are stable and valid, and that the process has been improved by making the choice easier for decision makers and by defining new and more comprehensive criteria for selection.

The Impact of Strategic Experiential Modules (SEMs) Dimension on Visitor's Revisit Intention: A Lesson from the Sunrise of Java, Indonesia: Acces la Success

Mangrove tourism is one of the tourist destinations offered by tourism managers that is currently gaining popularity and popularity among tourists. Keeping tourists coming back can be a very effective strategy for developing tourist destinations. This study employs Experiential Marketing as a strategy to increase tourist interest. Because research in the field of experiential marketing in nature tourism destinations such as mangrove tourism is still limited, the topics of this study are experiential marketing and visitor visit intention. The purpose of this study was to determine the impact of strategic experiential modules (SEMs) on visitor revisits intention. The research method used is quantitative with the variable dimensions of SEMs and visitor revisits intention, a sample of 93 tourists with a purposive sampling technique, and multiple linear regression analysis techniques. The results showed that the sense, act, and relate variables had a positive and significant impact on the visitor revisits intention, while the feel variable had a positive but not significant impact, and the think variable had a negative but not significant impact on the visitor revisits intention.

FAIR TAXATION UNDER THE GLOBAL ANTI-BASE EROSION RULES?

In 2021 the OECD launched the Global Minimum Company Tax to implement the Action 1 of the BEPS Project. This instrument has seen as a good mechanism to prevent company avoiding taxes at the global level and to stop existence of the harmful tax regimes worldwide, as well as a good mechanism to achieve fair taxation in the era of global digitalization. However, the broke-out of the COVID-19 pandemic and, consequently, the close of the national borders, then armed conflict between Russia and Ukraine, boost financial crisis and the crises in almost all social and industrial spheres at the global level. Such unwilling trend, between all, has influenced behavior of the companies and the initial optimism of the OECD and other international organizations that the global minimum company tax, at the very end, would end existence of the harmful tax regimes, tax avoidance and unfair taxation, dropped significantly. Therefore, at the very end of the 2022 and the beginning of the 2023, the OECD launched consultation document on tax certainty in the application of the Pillar Two of the global minimum tax known as a GloBE (Global Anti-Base Erosion) Model Rules. This paper deals with mentioned issue and actual problems that the application of the GLoBE rules is faced with.

Informational inefficiency on bitcoin futures

This paper investigates the dynamics and drivers of informational inefficiency in the Bitcoin futures market. To quantify the adaptive pattern of informational inefficiency, we leverage two groups of statistics which measure long memory and fractal dimension to construct a global-local market inefficiency index. Our findings validate the adaptive market hypothesis, and the global and local inefficiency exhibits different patterns and contributions. Regarding the driving factors of the time-varying inefficiency, our results suggest that trading activity of retailers (hedgers) increases (decreases) informational inefficiency. Compared to hedgers and retailers, the role played by speculators is more likely to be affected by the COVID-19 crisis. Extremely bullish and bearish investor sentiment has more significant impact on the local inefficiency. Arbitrage potential, funding liquidity, and the pandemic exert impacts on the global and local inefficiency differently. No significant evidence is found for market liquidity and policy uncertainty related to cryptocurrency.