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One of the adverse effects of COVID-19 is on poor economic and financial performance. Such economic underperformance, less demand from the consumer side and supply chain disruption is leading to stock market volatility. In such a backdrop, this paper aims to find the impact of COVID-19 on the Indian stock market by analyzing the analyst’s report.

The sample includes a cross-sectional data set on selected Indian firms that are indexed in BSE 100. The authors calculate the score of disclosure tone by using a textual analysis tool based on the analyst report of selected BSE 100 firms' approach in tackling COVID-19’s impact. The relationship between the tone of the analyst report and stock market performance is examined. This empirical model also survives robustness analysis to establish the consistency of the findings. This study uses both frequentist statistics and Bayesian statistics approach.

The empirical result shows that tone has negative and significant influence on stock market performance. This study indicates that either analysts are not providing value-relevant and incremental information, which can reduce the stock market volatility during this pandemic situation or investors are not able to recognize the optimism of the information.

This study provides an interesting insight regarding retail investors' stock purchasing behavior during the crisis period. Hence, this study also lays out crucial managerial implications that can be followed by preparers while preparing corporate disclosure.

In the concern on pandemic and its impact on the stock market, this study sheds light on investors' preferences during the crisis period. This study uniquely focuses on analyst reports and investors' preference which has not been studied widely. To the best of the authors’ knowledge, this is the first study in the Indian context, which aims to understand retail investors’ investment preferences during a pandemic.

This paper aims to examine the impact of six possible foreign direct investment (FDI) spillover channels on the total factor productivity (TFP) of Chinese agricultural enterprises and investigate the moderating role of absorptive capacity (technological acumen) on TFP spillover effects.

Based on data from 118 agricultural and related Chinese industries, the authors employ a multithreshold regression model to empirically analyze the impact of FDI on the TFP of agricultural enterprises and the threshold effect of absorptive capacity. To overcome potential endogeneity problems, the authors select the FDI stock of corresponding USA industries and the industrial access policy index as instrumental variables and re-estimate the model.

The results suggest foreign-invested agricultural enterprises are more likely to benefit from FDI, while the “aggregate” FDI spillover effect is negative for domestic agricultural enterprises. However, once threshold effects are introduced, the authors find firms “close to” (“far from”) the technological frontier experience statistically significant positive (negative) spillover effects. Similar results are obtained for virtually all FDI spillover channels for firms in both upstream and downstream industries. FDI spillovers, when they occur, can be a two-edged sword – benefiting some firms at the expense of others.

The authors introduce six FDI spillover channels to examine the impact of FDI on the productivity of foreign-invested and domestic agricultural enterprises. Moreover, the authors analyze the threshold effect of firms' absorptive capacity. These findings can help formulate foreign investment introduction policies based on the characteristics of agricultural enterprises with different ownership structures. These results are also beneficial for agricultural enterprises to better exploit FDI spillover effects and improve their productivity.

This study aims to determine how much company participation in a type of cluster affects its economic performance.

This study includes companies operating in seven industries (automotive, engineering, textiles, information technology (IT) services, furniture, packaging and nanotechnology) in the Czech Republic. The companies are divided into three groups: members of institutionalized cluster, operating in the same region (natural clusters) and operating in other regions. Data envelopment window analysis is used to measure their performance for 2009–2019.

Results show that the effect of clustering differs among industries. Companies in three industries (automotive, engineering, nanotechnology) reveal a positive impact of the cluster initiative on performance growth. Two industries (textile, packaging) with companies operating in a natural cluster show better performance than those in an institutionalized cluster. Moreover, the IT services and the furniture industries show no positive effect of clustering on corporate performance.

This research includes 686 companies from seven industries and monitored for 11 years. On the one hand, the sample includes a relatively high number of companies overall; but on the other hand, the sample is relatively small, especially for nonclustered companies. The reason is the lack of available financial statements for small companies.

From the perspective of practical cluster policy, the authors can recommend that monitoring the performance of member companies in clusters must be one of the criteria for evaluating the success of a cluster, such as cluster initiatives.

This study distinguishes between long-standing natural clusters in a given industry and institutionalized ones that have emerged because of a top-down initiative. An original database is created for clustered and nonclustered companies in seven industries, covering the entire Czech Republic.

This study aims to investigate the effects of peers on corporate payout policies in one of the largest emerging markets – India. It also examines the motives for mimicking payout decisions.

The sample is composed of 3,024 non-financial and non-government firms listed on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) for the period 1995 to 2020. To encounter the endogeneity problem, the instrumental variable technique based on peer firms' idiosyncratic risk is used to estimate the effects of peers on firms' payout policy. To define peer reference groups, the authors use the basic industry classification of the firms.

The results indicate a significant positive impact of peers on firms' dividend policies in India. A firm with all dividend-paying peers is more likely to declare dividends than the one with no dividend-paying peers. Further, peer effects are found to be more pronounced amongst larger and older firms, thus supporting the rivalry theory of mimicking.

To the best of the authors' knowledge, the present study is the first of its kind that attempts to understand peer effects on payout decisions in an emerging market India, that offers a unique institutional setting. Moreover, the authors extend the existing literature by investigating the peer effects on a firm's payout policies considering various firm-level characteristics, such as growth opportunity, cash holding, financial constraint and profitability, which previous studies have not taken into consideration. These results provide additional insights into the heterogeneity and motives behind peer effects.

This study aims to explore the spillover effects of data breaches from a consumer perspective in the e-commerce context. Specifically, we investigate how an online retailer’s data breach affects consumers’ privacy risk perceptions of competing firms, and further how it affects shopping intention for the competitors. We also examine how the privacy risk contagion effect varies depending on the characteristics of competitors and their competitive responses.

We conducted two scenario-based experiments with surveys. To assess the spillover effects and the moderating effects, we employed an analysis of covariance. We also performed bootstrapping-based mediation analyses using the PROCESS macro.

We find evidence for the privacy risk contagion effect and demonstrate that it negatively influences consumers’ shopping intention for a competing firm. We also find that a competitor’s cybersecurity message is effective in avoiding the privacy risk contagion effect and the competitor even benefits from it.

While previous studies have examined the impacts of data breaches on customer perceptions of the breached firm, our study focuses on customer perceptions of the non-breached firms. To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence for the negative spillover effects of a data breach from a consumer perspective. More importantly, this study empirically demonstrates that the non-breached competitor’s competitive response is effective in preventing unintended negative spillover in the context of the data breach.

The objective of this study is to explore the structural attributes of the pharmaceutical industry before the onset of the COVID-19 pandemic by examining the relationship between inventory and firm performance and developing a taxonomy of pharmaceutical firms based on the earns-turns matrix.

This study examines the inventory–firm performance linkage, considering both total inventory and its discrete inventory components in pharmaceutical firms. In addition, this research develops a new taxonomy of pharmaceutical firms based on the earns-turns matrix. A large panel dataset of firms in the US pharmaceutical industry was collected for the period 2000–2019.

The results reveal that strategic groups identified based on this taxonomy show different levels of profitability and inventory turns in the earns-turns matrix. Most pharmaceutical firms moved from the low-right to the top-left section in the earns-turns matrix, indicating that these firms have generally pursued profitability rather than effective inventory management.

This study explores the structural attributes of the pharmaceutical industry using the earns-turns matrix. This two-dimensional analysis may not, however, capture the full complexity of inventory–firm performance dynamics.

The mapping of strategic groups on the earns-turns matrix provides a useful tool for visual representations of the dynamics of strategic groups in terms of financial performance and inventory management performance. Practitioners can use the earns-turns matrix to benchmark their firm's position against their competitors.

This study broadens the scope of operations management research by introducing the earns-turns matrix as an empirical validation tool for operational and strategic management theories. This study emphasizes the effectiveness of the earns-turns matrix in analyzing strategic groups of pharmaceutical firms.

The pharmaceutical industry faces multiple risks that adversely affect its performance. Within these risks, some dependencies have been observed, which help in streamlining the mitigation efforts. Therefore, the present work identifies and categorizes various risks/sub-risks in cause–effect groups, considering uncertainty in the decision-making process.

An extensive literature review and experts' opinions were utilized to identify and finalize the risks faced by the pharmaceutical industry. For further analysis, data collection was done using a questionnaire focusing on finalized risks. Based on the data, the causal relation under uncertainty between various risks/sub-risks was identified using a multi-criteria decision making (MCDM) technique, i.e. intuitionistic fuzzy DEMATEL, in a pairwise manner.

The results show that the three most prominent risk categories are operational, demand/customer/market and financial. Also, out of the seven main risks, only supplier and operational are categorized within the effect group and the rest, i.e. financial, demand, logistics, political and technology within the cause group. The sub-risks within each category have also been categorized into cause–effect groups. The mitigation of cause group risks will help in economize the financial resources and improve the performance and resilience of the industry.

There is insufficient research on identifying the causality among the pharmaceutical industry risks. Additionally, an extensive discussion on the identified cause–effect groups is also missing in the literature. Therefore, in this work, efforts have been made to determine the prominent risks for the Indian pharmaceutical industry that will be helpful for channelizing the resources to mitigate risks for a resilient industry.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.

This study is devoted to examining the peer effects of engineering enterprises’ internationalization from the viewpoint of industry subdivision and how information and competition alter peer effects. Furthermore, the heterogeneity of peer effects is analyzed based on manager characteristics.

In this study, multiple regression analysis was conducted on a sample of 38 Chinese engineering enterprises listed in the Engineering News-Record’s top 250 international contractors over the period of 2013–2021. This study collected the paired data from the enterprise annual reports and the China Stock Market & Accounting Research database.

The results reveal that (1) there exist peer effects within the subdivided industry of the engineering field; the quality of information disclosure of peer enterprises and degree of market competition moderate the peer effects; (2) the peer effects of internationalization are more pronounced in engineering enterprises with managers who have lower ability, hold greater power or are older.

The findings of this study contribute to understanding the peer effect in the process of internationalization of engineering enterprises, and help enterprises to effectively supervise the irrational behavior of top managers, so as to develop better internationalization strategies.

The results extend peer effects to the subdivision industry of the engineering field. Furthermore, this study also enriches the relevant research on peer effects among enterprises by empirically supporting the moderating role of information and competition as well as analyzing the heterogeneity of the peer effects from the perspective of manager characteristics.

The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.

Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.

Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.

The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.

The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.