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Authors analyze a business model (BM) based on organizational performance. BMs are strategic tools used to achieve high performance. This study is based on two characteristics of causal complexity: conjunction and equifinality. Authors also examine the applicability of causal asymmetry in the relationship between BMs and organizational performance.

Generally, the relationship between BM elements and organizational performance is analyzed using a correlational approach. This relationship is marked by causal complexity, which cannot be analyzed via such approach. Authors applied a fuzzy-set qualitative comparative analysis with data from three time-periods and two performance variables for pharmaceutical firms.

Qualitative comparative analysis revealed that high performance resulted from configurations (combinations) of BM elements and not from the effects of individual elements. In addition, multiple configurations are available for achieving high performance. Causal asymmetry was observed in the configuration of the BM elements for high and low performances.

Using qualitative comparative analysis of data sets from three time-periods in the context of the pharmaceutical industry BM, authors integrated the theoretical constructs of causal complexity, namely conjunction, equifinality and causal asymmetry.

Findings related to conjunctions will help managers shift their focus from individual BM elements to combinations of BM elements. Additionally, the findings related to equifinality and causal asymmetry will allow flexibility in designing their company’s BM according to the resource constraints their company faces.

This was one of the first few studies on BMs using the twin indicators of the organizational performance relationship and causal complexity.

This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

The purpose of this research study was to understand the simultaneous competitive and social gains of machine learning (ML) and artificial intelligence (AI) usage in organizations. There was a knowledge hiatus regarding the contribution of the deployment of ML and AI technologies and their effects on organizations and society.

This study was grounded on the dynamic capabilities (DC) and ML and AI automation-augmentation paradox literature. This research study examined these theoretical perspectives using the response of 239 Indian organizational chief technology officers (CTOs). Partial least square-structural equation modeling (PLS-SEM) path modeling was applied for data analysis.

The results indicated that ML and AI technologies organizational usage positively influenced DC initiatives. The findings depicted that DC fully mediated ML and AI-based technologies' effects on firm performance and social performance.

This study contributed to theoretical discourse regarding the tension between organizational and social outcomes of ML and AI technologies. The study extended the role of DC as a vital strategy in achieving social benefits from ML and AI use. Furthermore, the theoretical tension of the automation-augmentation paradox was explored.

Organizations deploying ML and AI technologies could apply this study's insights to comprehend the organizational routines to pursue simultaneous competitive benefits and social gains. Furthermore, chief technology executives of organizations could devise how ML and AI technologies usage from a DC perspective could help settle the tension of the automation-augmentation paradox.

Increased ML and AI technologies usage in organizations enhanced DC. They could lead to positive social benefits such as new job creation, increased compensation to skilled employees and greater gender participation in employment. These insights could be derived based on this research study.

This study was among the first few empirical investigations to provide theoretical and practical insights regarding the organizational and societal benefits of ML and AI usage in organizations because of their DC. This study was also one of the first empirical investigations that addressed the automation-augmentation paradox at the enterprise level.

In the course of worldwide COVID-19, the phenomenon of corporate social responsibility (CSR) gained more importance and publicity. Many organizations made a significant contribution in dealing with the crisis situation and even increased their spending on the welfare activities. This study aims to evaluate the attitude of community, especially young generation, towards the CSR undertaken by the organization during the pandemic period.

Descriptive research design has been employed using purposive sampling for data collection through a structured questionnaire. A sample of 550 was taken, and pilot survey was conducted among 100 respondents before administering it at full scale. A model has been proposed and tested by using structural equation modelling in AMOS.

The results of the study show that compulsory provisions of CSR have enhanced the trust of community and made the organizations more responsive towards philanthropic, legal, ethical and economic responsibility. The respondents were found to be aware about the welfare activities carried out by the organizations and developed a positive attitude towards them.

First, the study is limited to examining the attitude of community towards CSR, especially young generation. Second, it is difficult to say whether outcomes of this study can be generalized for such other potential global crisis. Third, the study is based on the Carroll’s “CSR Pyramid” framework when other such frameworks and approaches could be available to analyse the impact of COVID-19-related CSR initiatives. Last, this study has been conducted only in the state of Maharashtra, and results may not be applicable to other states as well other countries.

The findings of the study may help the organizations to plan their activities in line with the amendments made time to time. This shall also help the regulating agencies to monitor and catch the wrongdoers and take appropriate action. Findings of such studies, based on public opinion, can also help the governments to make further amendments, time to time, in related acts. It can also be said that with the involvement of public/society, more transparency can be brought in the functioning of the organizations, especially in the context of CSR.

Earlier, most of the organizations were falsely recording the CSR expenditure in their balance sheets without actually spending it, but the amendment in act has made it compulsory for the organizations to follow it honestly. The pandemic period gave an opportunity to the society to evaluate the organizations on these parameters and to make their opinion about them in real time. Therefore, it is concluded that pandemic has created awareness in the society and significantly influenced their attitude about CSR activities. This shall also help the organizations feel a pressure in future while planning and implementing the activities under CSR.

The results of the study show contribution of the corporate towards social welfare during pandemic. The results would help the policymakers to monitor the execution of practices more closely and organizations to execute their strategies in a more effective manner.

The advent of robotics and automation technologies was augmenting firm initiatives to attain competitive advantage. From a resource-based view perspective, human-led capabilities were important to operate with technology resource base of an organisation. This was evident for both manufacturing as well as services firms. However, employees as an individual confronted technology anxiety (TA) when they were working with new technologies like robotics and automation technologies. Thus, the purpose of this paper was to examine the factors causing TA.

Given the novelty of this research study context a qualitative exploratory method was designed. For this research study, the data collected was through in-depth interviews conducted through open-ended semi-structured questionnaire. The data was collected from 62 frontline employees who were working with robotics and automation-based technologies in manufacturing firms. The authors applied thematic content analysis on collected data for analysis.

Technology anxieties ranged from fear of complete inability to learn new technologies, failure to learn new technologies properly, incapability to implement the learned skills and job loss to younger technology savvy employees. Finally, there was anxiety over job loss as automation and robotic technologies over the years was expected to erode the employment of human workforce altogether.

The author undertook the research study based upon the TA perspective advocated by Meuter et al. (2003) and Yang and Forney (2013). Furthermore, this research study in the context of robotics and automation-based technologies in the manufacturing sector applied the mental accounting theory (Thaler, 1999) and technology self-efficacy perspective (Huffman et al., 2013).

Managers involved in the implementation of robotics and automation-based technologies were required to address TA of employees. Fear of job loss had to be addressed specially in a country like India. Anxiety regarding the ability to learn to work with robotics and automation technologies also was needed to be addressed by managers through adequate training and time for preparation. The benefits of robotics and automation-based technologies for employees as well as organisations have to be ascertained through open communication between the management and the frontline employees.

To the best of the authors’ knowledge, this was one of the first empirical research studies which deliberated regarding TA in the context of frontline workers working with robotics and automation-based technologies in the manufacturing sector. This research study was based upon a combination of varied perspectives ranging from micro foundations theory, TA, mental accounting theory and technology self-efficacy perspective.

The literature on the influence of audit committees (AC) and cosmetic accounting (CA) is scarce. AC plays a unique and vital role in boosting earnings reliability in countries with weaker application of accounting standards or weaker legal protection for investors. AC, therefore, are considered to be one of the essential tools available to directors in supervising management decisions regarding financial reporting. This paper aims to examine the influence of AC characteristics (ACC) on CA and how this relationship is moderated by the audit fee.

This study used probit regression to analyze 1,218 firm-year observations of listed companies in Tehran Stock Exchange from 2014 to 2020.

The results show that AC financial accounting expertise, AC independence, female AC membership and AC tenure were negatively related to CA. The negative relationship is highly pronounced when a firm incurs higher audit fees, and audit fees moderate the relationship between ACC and CA. Results for the robustness checks show that only AC independence was significant, and the results of other characteristics were not significant.

This research was conducted in an Iranian setting where the formation of ACs is on the verge of regulation; therefore, the data used for the study only contains the seven-year period of ACs’ statutory activity. In addition, a lack of consensus on the precise measures of an AC’s effectiveness could be considered as a restrictive factor.

The findings provide an initial insight into the effect AC on CA and moderating effect of audit fee on the relationship between ACC and CA.

The purpose of this study is to investigate the impact of audit committee characteristics on firm performance. In particular, the authors employ the random-effects variant of the Hunter–Schmidt meta-analyze procedure to analyze the effects of key audit committee attributes, namely audit committee independence, audit committee expertise, audit committee size, audit committee meeting along with big four impact on firm performance. The authors hope to gain a better understanding of the function of audit committees in enhancing firm performance and to uncover potential discrepancies in prior findings due to varying economic levels or performance metrics.

This study uses the Hunter–Schmidt method to conduct a meta-analysis of 39 previous studies published between 2012 and 2022 to investigate the relationship between audit committee characteristics and firm performance.

The results indicate that audit committee independence, expertise, size and affiliation with the big four have a significant and positive effect on firm performance, while audit committee meetings have a non-significant effect. Furthermore, findings suggest that companies should carefully consider the contextual factors that may impact the effectiveness of their corporate governance structures, such as economic level, when designing and implementing governance mechanisms.

This study is significant as it is the first to combine and analyze previous research on this topic and highlights the importance of certain audit committee characteristics in enhancing financial reporting quality and corporate governance.

The objective of this research is to identify and prioritize the critical factors that influence the adoption of blockchain technology within the banking sector.

A well-known theoretical framework, the “Technology Organization Environment (TOE),” was chosen to analyze what criteria and sub-criteria affect blockchain adoption in the banking sector after a thorough assessment of the prior literature. Following that, 3 evaluation criteria and 14 sub-criteria were selected and verified using expert opinion. A survey design was created, and data for the study has been collected from various information technology (IT) managers/officers in the banking sector. A fuzzy analytic hierarchy process (Fuzzy-AHP) was then used to meet the purpose of the research.

The study identified that the organizational dimension is the most significant criteria for blockchain adoption in the banking sector, followed by the environmental dimension. In contrast, the technological dimension is the least influential criterion. Clientele pressure, IT resources, financial resources, pressure from competitors and relative advantage are the most influential sub-criteria for blockchain adoption.

This study provides valuable insights to bank managers, blockchain and IT developers, third-party service providers and policymakers. For instance, adopting the same blockchain platform is easier for both large and small banks for banking operations by using third-party service provider. At the same time, banks should have the banks' own core team to implement the blockchain-based systems or to have control over the third-party service providers during the adoption stage.

To the best of the authors' knowledge, no empirical studies have used a holistic organizational context to understand the factors influencing the adoption of blockchain technology from traditional to blockchain-based banking systems.