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Although the literature provides insights into the role of experiential learning based on prototypes in identification of latent customer need, it offers different views on the role of product prototypes in improving the efficacy of learning customer need, and also neglects the role of vicarious learning in prototype-based experiential learning. In a data-rich environment, market big data create new opportunities to learn from vicarious, digitalized experiences that are not observable with prototype-based learning. Therefore, the purpose of this study is to compare the effects of product prototype strategies – basic prototype strategy and enhanced prototype strategy – on identification of latent customer needs, and determine how each prototype strategy interacts with vicarious learning based on market big data to identify latent customer needs.

We collected data from 299 Chinese manufacturing firms via on-site surveys to explore our research question. All of our hypotheses were supported by the regression results.

This study finds that both the enhanced and basic prototype strategies (experiential learning from direct market experience based on prototyping) have positive effects on latent need identification, but the effect of enhanced prototypes is stronger. Furthermore, the enhanced and basic prototype strategies have different interaction effects with market big data (vicarious learning from indirect market experiences) on latent need identification.

This research extends the literature on prototype-based learning for latent need identification. It also contributes to the experiential prototype-based learning literature by exploring the role of vicarious learning based on market big data.

This paper aims to investigate the relationship between military connections and tax avoidance in Indonesia. Further, the paper examines whether the relationship between military connections and tax avoidance is impacted by three corporate governance variables: auditor size or Big 4, board size and audit committee independence. Indonesia's settings allow for a unique investigation, as military involvement has been documented.

This paper uses Indonesia as the research setting because its military forces have a long history of business involvement. The sample includes 1,986 firm-year observations on the Indonesia Stock Exchange from 2010 to 2018. The period signifies the time of significant change post-Suharto to illustrate changes in military reform.

Military-connected firms recorded a negative relationship with effective tax rates, indicating higher tax avoidance. The authors extend this test by considering three corporate governance variables: Big 4, board size and audit committee independence. They find the corporate governance variables are ineffective in mitigating the positive impact of military-connected firms and corporate tax avoidance. The results remain consistent when performing endogeneity tests.

This paper adds to the extant literature by examining the impact of military connections on tax avoidance. The findings reflect Indonesia's institutional settings depicting military and political connections.

The process performed during a financial statement audit is critical but is unobservable to external stakeholders. This can create challenges in assessing the quality of individual audit engagements. This study’s objective is to introduce and investigate an archival measure based on publicly available information that proxies for audit process ineffectiveness.

We proxy for audit process ineffectiveness using errors in the audit report. We examine audit reports to identify errors because the audit report represents the auditor’s primary communication with financial statement users and is subject to rigorous preparation and review. We first examine if typical factors influencing audit process ineffectiveness are associated with audit report errors. We then examine whether audit reports containing errors are associated with audit quality measures.

We find that errors are more likely to be present in audit reports when time pressure exists and less likely when auditors exert more effort and when audit engagement risk is higher. Results also show that errors in audit reports are positively associated with financial reporting misstatements, measured by subsequently disclosed Big R restatements and out-of-period adjustments.

Collectively, our evidence suggests that an audit report containing an error is a suitable proxy for audit process ineffectiveness. This proxy has audit quality implications because inattentiveness in one area of the audit process could indicate inattentiveness in another area.

This paper aims to investigate the impact of audit mechanisms on earnings management (EM) practices in listed Saudi Arabian companies. Specifically, it examines the association between audit committee (AC) characteristics, external audit quality and EM before and after the revision of Saudi Regulations on Corporate Governance (SRCGs) in 2017.

The study analyzes a data set comprising 135 Saudi-listed companies observed from 2013 to 2020. EM practices are measured using the absolute value of discretionary accruals, and external audit quality is assessed by the involvement of BIG 4 auditors. The authors also consider four variables to gauge AC characteristics: independence, size, meeting frequency and expertise. To test the hypotheses, the authors use multivariate regression on panel data.

The findings provide robust evidence regarding the impact of audit mechanisms on EM practices. The presence of accounting and finance experts within the AC is shown to have a substantial and statistically significant effect in reducing EM practices. Similarly, AC independence demonstrates a negative association with EM after the implementation of the SRCGs 2017. However, the study does not uncover any statistically significant impact of AC size and meeting frequency on EM practices. Moreover, the research highlights a noteworthy positive relationship between EM practices and engagement with BIG 4 audit firms before the SRCGs 2017. However, this relationship ceases to exist following the regulatory amendment.

The practical implications of this research are significant for policymakers and companies operating in Saudi Arabia, as well as for practitioners and auditors working in the region. The findings underscore the importance of high-quality auditing work to prevent EM practices and promote transparent financial reporting. The study recommends increasing the number of independent members and financial experts on the AC, as well as rigorous monitoring of AC size and meetings. It also emphasizes the need for compliance with governance regulations to focus on effective monitoring of the AC rather than mere fulfillment of requirements.

The study enhances the existing literature on the effectiveness of ACs and external audit quality in mitigating EM by providing evidence from a unique and Islamic context that has not been extensively studied before. This can help in validating or challenging the findings of previous studies and provide a more comprehensive understanding of the factors that impact EM in different contexts.

This study aims to find out the role of big data in the field of library and information science by considering the opportunities and challenges.

This study, which was conducted on a desk, examined the rise and significance of big data in the field of library and information science in Nigeria. Also, systematic literature review is done, exploring blogs and wikis to gather data on the use of big data.

This study emphasizes that as data is the primary component in the creation of information, professionals in the fields of library and information science must develop the knowledge and abilities necessary to support big data analysis. It was determined that offering and facilitating big data analysis would guarantee our place as a priceless and crucial resource in the digital workplace.

To the best of the authors’ knowledge, this study will be one of its kind to examine the role of big data in the field of library and information science profession. Furthermore, the results of the study will expose librarians and information professionals on the opportunities and challenges inherent in the use of big data technologies.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

Initial Public Offering (IPO) is a major milestone for a company. It allows a private company to issue shares to a much broader group of investors and become public. But conclusive evidence of the driving forces behind investors’ demand is yet to be identified. Therefore, the major purpose of this study is to assess the level of investors’ demand in IPO and how investors’ demand in IPOs is affected.

The study will employ 80 IPO companies of a Muslim-majority country, Bangladesh, starting from 2013 to 2021 with application of linear and quantile regressions. Apart from that, t-test will be used to compare means of groups of Shariah-compliant and non-Shariah-compliant firms and IPOs under fixed-price and book-building mechanism.

Oversubscription is higher for IPOs issued through fixed-price method compared to book-building method, but no significant difference is found in oversubscription for Shariah firms compared to non-Shariah firms based on t-tests. The authors found IPO size, firm size, IPO risk, proportion of shares offered to public, and bank interest rate to have significant impact on the IPO demand. Some models found non-Shariah compliance status of IPO companies to be a significant factor for the investors to demand IPO. Quantile regression results found board independence to have a positive association with larger, less-subscribed firms and board size to have a negative relation with IPO demand, for smaller firms with high demand.

Future studies may apply the findings to other settings, especially into the reasons behind preference for non-Shariah-compliant firms and higher demand for IPOs during higher interest rate. Equity issuing firms and issue managers can benefit from this study by wisely deciding on the proportion of shares for public, issue size and board of director composition. Shariah considerations cannot be ignored given that more information on Shariah compliance is disseminated among investors despite current non-preference for Shariah-compliant IPOs. On the other hand, institutional investors and general investors should consider firm-specific, governance and macroeconomic factors in IPO investment. Likewise, regulators would do well to bring in quality IPOs with characteristics mentioned in this study for ensuring stability of the market.

The main contribution of the study is identifying determinants of IPO demand: faith, governance, macro issues – understanding whether one or many of the above factors drive investor demand in IPOs of a Muslim-majority country will be the main contribution.

This paper analyzed the effect of voluntary corporate disclosure on firm value and how audit quality and cross-border stock market listing moderate this relationship.

The paper analyzed S&P BSE index constituents’ 90 Indian enterprises for 2017–2019. The India Disclosure Index Report was used to fetch the voluntary disclosure scores. Further, the study was conducted in two parts using six different panel-data regression models in the framework of legitimacy, agency, signaling and market segmentation theory. First, the study investigated the direct impact of voluntary disclosures on return on assets (ROA) and Tobin’s Q. Second, the moderating effect of the “Big 4” was tested. Third, the paper also examined the moderating role of “cross-border stock market listing” in the direction of voluntary disclosure-firm value relationships.

Primarily, the results postulate a significant positive impact of voluntary disclosures on ROA and Tobin’s Q. A higher voluntary disclosure leads to a higher ROA and Tobin’s Q for firms. Moreover, the improvement effect of such disclosures on ROA and Tobin’s Q is more pronounced for companies “listed abroad” and audited by “Big 4.”

The findings will enhance managers’ learning about the financial impact of voluntary disclosures. The choice of a “Big 4” and “Cross border stock market listing” indicates firms’ future positive perspectives, strengthening investor trust in the market.

The results suggest that companies’ potential auditing, agency and litigation issues could be addressed through fairness in the information content of voluntary disclosures.

This examination presents a firm valuation model in which voluntary disclosure tackles an ethical issue, the resolution of which depends on the “audit quality” and “cross-border stock market listing.”

In the era of big data, there is doubt about the significance of causal inference as a paramount scientific task in the social sciences. Meanwhile, data-mining techniques rooted in big data and artificial intelligence (AI) have infiltrated numerous aspects of social science research. This study aims to expound the criticality of discerning causal relationships – beyond mere correlations – and scrutinizes the ramifications of big data and AI in the identification of causality.

This study discusses the challenges and opportunities for causality identification in the era of big data under the framework of potential outcomes model and structural causal model.

First, even in the age of big data, correlations that lack interpretability, robustness and feasibility cannot substitute causality. Second, the richness of the sample size does not help solve the problem of systematic bias in the process of causal inference. Furthermore, current AI research targets correlations rather than causality, thus creating difficulties in advancing from observations to counterfactuals.

This study provides insights into the impact of big data era on causal inference in the social sciences, with a view toward enhancing the pool of theoretical concepts available to researchers in relevant fields and accurately guiding the direction of scientific research in these fields.

Despite the recognition that contextual factors play a key role in shaping individuals’ work-family (WF) interface, empirical research that simultaneously considers individual, roles and contextual factors is scarce. Drawing on the pyramid model of work-home interface, we delve into the intersection among sex, gender role ideology (GRI) and urbanization (URB) in relation to WF conflict and enrichment in India. Specifically, we explored whether and how sex (male vs female), GRI (traditional vs egalitarian) and URB (big vs small city) interact to predict WF conflict and WF enrichment.

The data were collected from 586 full-time employees working in both more and less urbanized cities in India. Moderation analyses were utilized to study the interaction effects on WF conflict and enrichment.

Results indicate that GRI is a stronger driver of WF experiences, especially WF enrichment, for women regardless of location. The study contributes to the understanding of WF experiences in India and addresses the complexity of WF experiences, especially with respect to sex and gender.

Our study offers a nuanced understanding of WF experiences in India by integrating micro- to macro-level antecedents, thereby addressing the complexity of WF experiences. While a lot of research explains sex and gender differences in WF experiences, our study highlights how these experiences vary with the degree of URB.