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.

Spatial Interactions and the Spread of COVID-19: A Network Perspective

We use unique data on the travel history of confirmed patients at a daily frequency across 31 provinces in China to study how spatial interactions influence the geographic spread of pandemic COVID-19. We develop and simultaneously estimate a structural model of dynamic disease transmission network formation and spatial interaction. This allows us to understand what externalities the disease risk associated with a single place may create for the entire country. We find a positive and significant spatial interaction effect that strongly influences the duration and severity of pandemic COVID-19. And there exists heterogeneity in this interaction effect: the spatial spillover effect from the source province is significantly higher than from other provinces. Further counterfactual policy analysis shows that targeting the key province can improve the effectiveness of policy interventions for containing the geographic spread of pandemic COVID-19, and the effect of such targeted policy decreases with an increase in the time of delay.

Detection of Multiple Structural Breaks in Large Covariance Matrices

This article studies multiple structural breaks in large contemporaneous covariance matrices of high-dimensional time series satisfying an approximate factor model. The breaks in the second-order moment structure of the common components are due to sudden changes in either factor loadings or covariance of latent factors, requiring appropriate transformation of the factor models to facilitate estimation of the (transformed) common factors and factor loadings via the classical principal component analysis. With the estimated factors and idiosyncratic errors, an easy-to-implement CUSUM-based detection technique is introduced to consistently estimate the location and number of breaks and correctly identify whether they originate in the common or idiosyncratic error components. The algorithms of Wild Binary Segmentation for Covariance (WBS-Cov) and Wild Sparsified Binary Segmentation for Covariance (WSBS-Cov) are used to estimate breaks in the common and idiosyncratic error components, respectively. Under some technical conditions, the asymptotic properties of the proposed methodology are derived with near-optimal rates (up to a logarithmic factor) achieved for the estimated breaks. Monte Carlo simulation studies are conducted to examine the finite-sample performance of the developed method and its comparison with other existing approaches. We finally apply our method to study the contemporaneous covariance structure of daily returns of S&P 500 constituents and identify a few breaks including those occurring during the 2007–2008 financial crisis and the recent coronavirus (COVID-19) outbreak. An package "” is provided to implement the proposed algorithms.

The spread of COVID-19 in stock returns along global value chains

This paper examines the performance of industries in the trade network in international stock markets during the onset of COVID-19. In general, the value of all industries in G20 countries declines significantly in the pandemic. Stock returns of industries in the central positions of global value chains exhibit remarkable resilience despite the economic hardship caused by COVID-19. This pattern is more pronounced when the disruptions caused by social distancing requirements are considered. We postulate that this is related to the essential services provided by the central industries.

Mediating and moderating effects of task interdependence and creative role identity behind innovation for service: evidence from China and Australia

PurposeInnovation for service contributes to service quality and customer satisfaction, and further benefits service-centered organizations to sustain competitive advantages. However, concurrent mediating and moderating mechanisms underlying innovation for service at both the group and individual levels have been scarcely investigated. The purpose of this study is to explore multilevel mediating and moderating mechanisms behind the relationship between dual-level transformational leadership (TFL) and innovation for service at the group and individual levels.Design/methodology/approachData were collected from two countries (i.e. China and Australia). Multilevel structural equation modeling was employed to validate the research model. Bootstrapping with 5,000 replications and latent moderated structural equation modeling were used to respectively examine the mediating and moderating mechanisms.FindingsThe cross-national results showed that task interdependence and creative role identity respectively played as the group-level and individual-level mediating roles between TFL and innovation for service. It was also found that task interdependence played as a cross-level predictor enhancing individual innovation for service. Task interdependence was a moderator on the relationship between individual-level TFL and creative role identity among Australian employees, but not among Chinese employees. The relationship between creative role identity and individual innovation for service was not moderated by task interdependence among both Chinese and Australian employees.Originality/valueThis study contributes to advancing the TFL–innovation research through revealing dual-level TFL as the antecedent of innovation for service at both the group and individual levels. It also extends the understandings of the mediating and moderating mechanisms behind this dual-level relationship between TFL and innovation for service.

A hybrid metaheuristic algorithm for the multi-objective location-routing problem in the early post-disaster stage

Disasters such as earthquakes, typhoons, floods and COVID-19 continue to threaten the lives of people in all countries. In order to cover the basic needs of the victims, emergency logistics should be implemented in time. Location-routing problem (LRP) tackles facility location problem and vehicle routing problem simultaneously to obtain the overall optimization. In response to the shortage of relief materials in the early post-disaster stage, a multi-objective model for the LRP considering fairness is constructed by evaluating the urgency coefficients of all demand points. The objectives are the lowest cost, delivery time and degree of dissatisfaction. Since LRP is a NP-hard problem, a hybrid metaheuristic algorithm of Discrete Particle Swarm Optimization (DPSO) and Harris Hawks Optimization (HHO) is designed to solve the model. In addition, three improvement strategies, namely elite-opposition learning, nonlinear escaping energy, multi-probability random walk, are introduced to enhance its execution efficiency. Finally, the effectiveness and performance of the LRP model and the hybrid metaheuristic algorithm are verified by a case study of COVID-19 in Wuhan. It demonstrates that the hybrid metaheuristic algorithm is more competitive with higher accuracy and the ability to jump out of the local optimum than other metaheuristic algorithms.

An integrative framework for building organizational resilience through environmental scanning: a view of organizational information processing theory: MRN

PurposeThis study aims to investigate the impact of environmental scanning on organizational resilience through the mediation of organizational learning and innovation based on organizational information processing theory (OIPT) within Egyptian small and medium enterprises (SMEs) during the COVID-19 pandemic.Design/methodology/approachThis study adopted a cross-sectional design to collect the data used to carry out mediation analysis. A self-administered questionnaire was used to collect data from a sample consisting of 249 Egyptian SMEs. The smart partial least square structural equation modeling (PLS-SEM) technique was adopted to test the hypotheses.FindingsEnvironmental scanning does not have a direct effect on organizational resilience. However, organizational learning and innovation fully mediate the relationship between environmental scanning and organizational resilience.Research limitations/implicationsThe sample size was small, covering only Egyptian manufacturing SMEs. The results may differ in the service sector and other countries. The study was cross-sectional which is limited to tracing the long-term effects of environmental scanning, organizational learning and innovation on organizational resilience. Accordingly, a longitudinal study may be undertaken.Practical implicationsManagers in Egyptian SMEs should use signals from environmental scanning activities as input for learning and transforming business processes through innovation to develop organizational resilience.Originality/valueThis study is the first to investigate the role of environmental scanning in building organizational resilience through organizational learning and innovation based on the perspective of OIPT within Egyptian SMEs during the COVID-19 crisis.

A real options approach to growth opportunities and resilience aftermath of the COVID-19 pandemic

PurposeFacing the challenges posed by the pandemic of COVID-19, this paper aims to contribute to the resilience of businesses through the development of a real options approach (ROA) that provides alternatives and opportunities for a decision process under situations when future events and outcomes are unknown and not capable of being known from current information.Design/methodology/approachThis paper involves a stochastic modelling process in generating a set of absolute option values, using available data and scenarios from the COVID-19 pandemic event. The modelling and simulations using ROA suggest how strategic portfolios resolve the growing problem during the endemic to all but in the most isolated societies.FindingsThis study finds the emergent correlation between circuit breakers and lockdowns, which have brought about a "distorted gravity” effect (inverse growth of global businesses and trades). However, "time-to-build” real options (i.e. deferral, expand, switch and compound exchange) start to function in the adaptive-transformative capabilities for growth opportunities of both government and corporate sectors. Significantly, some sectors grow faster than others while the compound exchange remains primarily challenging. Clearly, the government and corporate sectors are entangled, inevitably, the decoherence allows for the former to change uncertainty in the latter;therefore, government sector options change option values in the corporate sector.Originality/valueThe ROA by empirically focusing on both government and corporate sectors demonstrates under conditions of uncertainty how options in decision-making generate opportunities that hitherto have not been recognised and exercised upon by research in the immediate context of the COVID-19 pandemic. Importantly, the ROA provides an insightful concatenation (capability–behaviour approach) that drives resilience.

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.

Consumers' perceived value and use intention of cashless payment in the physical distancing context: evidence from an Asian emerging market

PurposeCOVID-19 and its measures such as physical distancing have shifted consumer payment behaviors toward cashless payment. Physical distancing is likely to remain a norm for some time to come and will be relevant in any future pandemics. This study aims to examine the impact of consumers' perceived value of cashless payment on their use intention in the physical distancing context, with the mediating role of psychological safety and the moderating role of trust propensity.Design/methodology/approachThis study used a survey method to obtain data from 690 consumers in an Asian emerging market, i.e. Vietnam. The data were analyzed using different statistical methods, including structural equation modeling.FindingsResults show that perceived value of cashless payment positively affects use intention, and this effect is mediated by psychological safety. Furthermore, trust propensity has a positive moderating effect on the link between perceived value and psychological safety.Practical implicationsThis study's findings provide implications for retailers and other stakeholders in implementing and promoting cashless payment systems, especially in the physical distancing context.Originality/valueThis study is among the first attempt to explain the relationships between consumers' perceptions, feelings of psychological safety and use intention toward cashless payment in the physical distancing context. The study's findings may also be relevant to any future pandemics.

Task-Technology Fit and ICT Use in Remote Work Practice During the COVID-19 Pandemic

This study examines the use of information and communications technology (ICT) in remote work practice during the COVID-19 pandemic by integrating task-technology fit theory and the post-acceptance model of IS continuance into a research framework. In addition, it operationalizes the technological characteristics of TTF (task-technology fit) with the technology acceptance model (TAM) and the diffusion of innovation (DOI) theory. The methodology to test the research model takes support from the partial least squares structural equation modeling (PLS-SEM) method using a sample of 320 employees. The results show that TAM significantly explains TTF. Furthermore, there is a positive impact of ICT use on individual and organizational performance. User satisfaction has the most significant effect on individual performance, organizational performance, and IS continuance intention. The authors provide some managerial implications for addressing the challenges of remote work related to ICT disruptions for the post-COVID-19 period.

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.

The Antecedents of Consumer Satisfaction Toward OTT Platforms During COVID-19 Lockdown in India

The outbreak of COVID-19 has emerged as the biggest threat to human life. It has changed the entire lifestyle of human beings concerning their emotional stability and cognitive development. Enjoyment is one of the emotions and acts as a positive stimulus that a consumer used to feel and seeks for a balanced life. Since the nationwide lockdown was implemented on March 25, 2020, people have turned restless about how to enjoy themselves at home, as all of their options of going out were being shattered. It was the time when continuous innovations in the form of digital content through over-the-top (OTT) platforms flourished and provided an affordable and diversified entertainment source to consumers. These OTT services help consumers to view the contents via the Internet directly. Furthermore, it has drastically changed people's preferences toward diversified content based on their choices. This study aims to explore the various determinants affecting consumer satisfaction toward the OTT platforms amid COVID-19 crisis in India. The study's main findings revealed that among the demographic variables, age group of the consumer largely influences their satisfaction toward OTT platforms. Moreover, work from home, affordability, convenience, and content quality are the significant determinants affecting consumer satisfaction levels toward OTT platforms. The study is relevant to the current marketing scenario, as it provides useful insights for the content developers of the major OTT platforms such as Amazon Prime, Netflix, Disney+ Hotstar, Voot, and many others to enhance the consumer satisfaction in the terms of digital content consumption.

Women in the Workplace: COVID-19 and Work-Life Balance: JMI

The COVID-19 pandemic has cost the lives of an enormous number of individuals around the world, isolated people, and disrupted businesses. These are the direct and devastating consequences of the disease, however there are other peripheral impacts as well. The pandemic is continuing to threaten the work-life balance (WLB) of employees, disrupting their domestic lives, intensifying their general stress levels, and impacting their ability to focus on their careers. This is a significant problem for both working women as well as men, however this study suggests the negative impact is more disruptive to women. Women represent approximately 46% of the human resources for organizations and they are major contributors to advancements in domains such as healthcare, education, government, and commercial development. Organizations, as a defensive measure, need to adapt policies and procedures in an attempt to moderate the disruptive influences the virus is having on their human resources. This paper explores the extant literature and defragments diverse COVID-19 studies to capture an overall picture of the unique impact the pandemic is having on working women. A qualitative study involving semi-structured in-depth interviews with 20 professional women was conducted. Interviews were reviewed holistically with themes across interviews identified. Resulting themes include WLB expectations post-COVID-19, childcare, employers and expectations, and return to work. Thematic findings are discussed and observations relative to organizational implications are provided. Also offered are thoughts and suggestions for the enhancement of WLB, thereby benefiting both women and their organizations.

A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies

Several procedures to forecast daily risk measures in cryptocurrency markets have been recently implemented in the literature. Among them, long‐memory processes, procedures taking into account the presence of extreme observations, procedures that include more than a single regime, and quantile regression‐based models have performed substantially better than standard methods in terms of forecasting risk measures. Those procedures are revisited in this paper, and their value at risk and expected shortfall forecasting performance are evaluated using recent Bitcoin and Ethereum data that include periods of turbulence due to the COVID‐19 pandemic, the third halving of Bitcoin, and the Lexia class action. Additionally, in order to mitigate the influence of model misspecification and enhance the forecasting performance obtained by individual models, we evaluate the use of several forecast combining strategies. Our results, based on a comprehensive backtesting exercise, reveal that, for Bitcoin, there is no single procedure outperforming all other models, but for Ethereum, there is evidence showing that the GAS model is a suitable alternative for forecasting both risk measures. We found that the combining methods were not able to outperform the better of the individual models.

Analyzing the research trends of COVID-19 using topic modeling approach

PurposeThe COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.Design/methodology/approachThe current study identifies the focus areas of the research conducted on the COVID-19 pandemic. s of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.FindingsBased on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.Originality/valueWhile similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.

Modelling COVID-19 effect on the performance of MENA Health-care sector

PurposeThis study models the effects of the COVID-19 pandemic on the performance of the private health-care sector in the Middle East and North Africa (MENA) countries. This paper aims to address the economic, societal and sustainability of the health-care sector.Design/methodology/approachData were collected from Bloomberg and the sample consists of 534 firm-year observations from 55 firms listed over 2010–2020. The authors apply panel data and control for the country and governance effects.FindingsThe authors found heterogeneous results regarding the three sub-sectors. The pandemic has a negative effect on the accounting and market performances of the "Pharmaceutical companies” and an insignificant impact on "Healthcare Management and Facilities Services.” Moreover, the impact of COVID-19 on health-care firms' performance depends on the country's economic classification and the degree of regulatory and governance frameworks.Research limitations/implicationsFurther studies may consider a larger sample and other regions. It is recommended to address the health-care sector's challenges to invest in new technologies such as "digital twin” and predictive and personalized medicine. It is worth testing model development theory and its effects on speeding up and designing models to ensure the proper functioning and developing mathematics to determine uncertainties in patient data and model predictions.Originality/valueTo the best of the authors' knowledge, this paper is novel as it is unique in modeling the impact of COVID-19 on the health-care public companies in the MENA region. The findings pinpoint firms' and countries' heterogeneous impacts on financial and market performances.

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.

Supplier selection framework to evade pseudo-resilience and to achieve sustainability in supply chains

PurposeDue to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.Design/methodology/approachA combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.FindingsThe authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.Originality/valueTo the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.