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Recent studies suggested the ratio of option to stock volume reflected the private information. Informed traders were drawn to the options market for its leverage effect and relatively low transaction costs. Informed traders use different intervals of option moneyness to execute their strategies. The question is which types of option moneyness were traded by informed traders and what information was reflected in the market. In this study, the authors focused on this question and constructed a method for capturing the activity of informed traders in the options and stock markets.

The authors constructed the daily measure, moneyness option trading volume to stock trading volume ratio (MOS), to capture the activity of informed traders in the market. The authors formed quintile portfolios sorted with respect to the moneyness option to stock trading volume ratio and provided the capital asset pricing model and Fama–French five-factor alphas. To determine whether MOS had predictive ability on future stock returns after controlling for company characteristic effects, the authors formed double-sorted portfolios and performed Fama–Macbeth regressions.

The authors found that the firms in the lowest moneyness option trading volume to stock trading volume ratio for put quintile outperform the highest quintile by 0.698% per week (approximately 36% per year). The firms in the highest moneyness option trading volume to stock trading volume ratio for call quintile outperform the lowest quintile by 0.575% per week (approximately 30% per year).

The authors first propose the measures, moneyness option trading volume to stock trading volume ratio, that combined with the trading volume and option moneyness. The authors provide evidence that the measures have the predictive ability to the future stock returns.

This paper aims to investigate the effect of gamified e-service quality (GE-SQ) on customer value co-creation, relationship quality and purchase intention in e-retailing.

A questionnaire was used to collect data from a sample of 549 e-retailing customers who participated in a gamified online service process. A structural equation modeling approach was adopted to analyze the model.

The empirical evidence confirmed that GE-SQ encouraged customer value co-creation behavior and relationship quality. Customer value co-creation and relationship quality led to higher purchase intention. Also, value co-creation and relationship quality partially mediated the relationship between GE-SQ and purchase intention.

The findings increase our knowledge of GE-SQ and its behavioral consequences. Moreover, the study proposes and validates a theoretical framework based on GE-SQ, value co-creation and customer relationship quality. This study provides insight into using gamification as a practical tool in the e-retailing industry.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Countries worldwide aim to improve their comparative advantages by efficiently using scarce resources for economic growth and development. While many studies have been conducted to measure intellectual capital at the firm's level, measuring it at the national level has been under-examined. In addition, while the important role of national intellectual capital in economic growth has been theoretically recognized in literature, this important link has largely been ignored in empirical analyses.

This study uses the newly developed index of national intellectual capital from Vo and Tran's (2022) study to examine its effects on national economic growth in the long run. The dynamic common correlated effects technique and the pooled mean group estimation are used on the sample of 23 economies in the Asia–Pacific region from 2000 to 2020.

Findings from this study confirm the positive and significant contribution of the national intellectual capital to economic growth in the region. The authors also find that, as a feedback effect, economic growth will also enhance and improve the accumulation of national intellectual capital.

The findings of this paper provide valuable evidence and implications for policymakers in managing and improving national intellectual capital in the Asia–Pacific region.

To the best of the authors’ knowledge, this is the first empirical study to examine the impact of national intellectual capital on economic growth in the long run in the Asia–Pacific economies.

This paper aims to explore how the role of the perception of good public governance reduces tax evasion (TE). Besides, this study investigates whether the nexus of public governance and TE differs between developed and developing economies.

Apart from the ordinary least squares (OLS) model, this study uses the linear mixed modeling technique. The World Governance Indicators and the multiple causes estimation (MIMIC) method are used to measure public governance. The shadow economy is used as a proxy for TE.

The results show that people's perceptions of public governance and the quality of government institutions are core elements that influence tax-evasion behavior. Besides, the rule of law (RoL) and political stability (PS) significantly impact tax-evasion behavior in developing countries. Nevertheless, the RoL, the control of corruption and PS are the most critical tax-evasion determinants among public governance indicators for developed countries. Regulatory quality shows a substantial positive relationship with TE in developed but not developing countries.

This paper provides a guide for policymakers on reducing tax-evasion behavior by paying more attention to maintaining the RoL and PS and fighting corruption. Additionally, this study highlights the importance of people's perceptions of the government's pursuit of the above policy-related improvements, which, in turn, affect their tax behavior.

To the best of the authors’ knowledge, this study is the first to explore the role of people's perceptions of improvements in public governance and how this can reduce TE behavior in developed and developing economies. Unlike prior studies, this study used the linear mixed model method, which is more advantageous than OLS and produces robust estimators.

With the advancement of technology, microlearning has emerged as a promising method to improve the efficacy of teaching and learning. This study aims to investigate the document types, volume, growth trajectory, geographic contribution, coauthor relationships, prominent authors, research groups, influential documents and publication outlets in the microlearning literature.

We adapt the PRISMA guidelines to assess the eligibility of 297 Scopus-indexed documents from 2002 to 2021. Each was manually labeled by educational level. Descriptive statistics and science mapping were conducted to highlight relevant objects and their patterns in the knowledge base.

This study confirms the increasing trend of microlearning publications over the last two decades, with conference papers dominating the microlearning literature (178 documents, 59.86%). Despite global contributions, a concentrated effort from scholars in 15 countries (22.39%) yielded 68.8% of all documents, while the remaining papers were dispersed across 52 other nations (77.61%). Another significant finding is that most documents pertain to three educational level categories: lifelong learning, higher education and all educational levels. In addition, this research highlights six key themes in the microlearning domain, encompassing (1) Design and evaluation of mobile learning, (2) Microlearning adaptation in MOOCs, (3) Language teaching and learning, (4) Workflow of a microlearning system, (5) Microlearning content design, (6) Health competence and health behaviors. Other aspects analyzed in this study include the most prominent authors, research groups, documents and references.

The finding represents all topics at various educational levels to offer a comprehensive view of the knowledge base.

This study examines the effect of business group affiliations on corporate cash holdings and how political connectedness modifies the relationship between business group affiliations and corporate cash holdings.

The multiple ordinary least square regression with year dummies is used to estimate the effect of business groups on cash holdings. For moderating, the multiplicative term is used. The data from 252 non-financial firms listed on Pakistan Stock Exchange were collected for the analysis from 2010 to 2018.

The findings show that business group affiliations negatively affect corporate cash holdings, and political connection positively moderates this relationship. Business group firms that are politically connected hold less cash. The firm-specific factors such as leverage, size, cash flow, and dividend dummy also significantly affect corporate cash holdings.

The results imply that affiliated companies have lessened financing frictions and improved stability in their expected future cash flows. Moreover, the results indicate that political connection minimizes the opportunity and agency costs linked to cash holdings.

This study contributes to the existing literature by examining the moderating role of political affiliations on the relationship between business groups and cash holdings in the emerging market.

The purpose of this study is to examine the impact of country-level governance on sustainability performance, taking into account the effect of sustainable development goals (SDGs) and board characteristics.

This study uses panel data analysis using fixed effect models to investigate the influence of country-level governance on sustainability performance while considering the effect of SDGs and board characteristics. The sample comprises 8,273 firms across 41 countries during the period spanning from 2016 to 2021. The sample is divided into two categories based on the score of SDGs.

The findings of this study show that countries with high SDGs score have better overall country-level governance and board attributes which have a statistically significant positive impact on sustainability performance. However, for those countries with low SDGs, political stability shows a statistically insignificant and negative impact on sustainability performance, while government effectiveness indicates a statistically insignificant positive impact on sustainability performance.

This study contributes to the literature by providing empirical evidence on the relationship between country-level governance, SDGs, board characteristics and sustainability performance. The study also highlights the importance of considering the effect of SDGs on the relationship between country-level governance and sustainability performance. The findings of this study could be useful for policymakers and firms in improving their sustainability performance and contributing to sustainable development.

This paper aims to examine the performance efficiency of 56 real estate assets within the rental sector in the UAE to evaluate the relative operation efficiency in relation to revenue generation.

The data envelopment analysis (DEA) approach was used to measure the relative operational efficiency of the studied assets in relation to the revenue performance. This method could produce a more informed and balanced approach to performance measurement.

The outcomes show that scores of efficiencies ranging from 7% to 99% in some of the models. The results showed that on average buildings are 75% relatively less efficient in maintenance, in term of revenue generation, than the benchmark set. Likewise, on average, the inefficient buildings are 60% relatively less efficient in insurance. Result also shows that 95% of the building assets in the sample are by and large operating at decreasing returns to scale. This implies that managers need to considerably reduce the operational resources (input) to improve the levels of revenue.

This study recommends that the FM operational variables that were found to inefficiently contribute to the revenue should be re-examined to test the validity of the findings. This is necessary before generalising or interpolating the results that are presented in this study.

The information obtained about operational performance can help FM managers to understand which improvements in the productivity of inefficient FM resources are required, providing insight into how to reduce operating costs and increase revenue.

This paper adds value in using new FM operational parameters to evaluate the efficiency of the performance of built assets.

Blockchain technology (BCT), since its emergence touted to be disruptive, is gaining momentum, especially in the agri-food system owing to its multiple benefits.

The authors attempted to conduct a systematic bibliometric visualization analysis of the BCT in the agri-food system. The analysis investigated the list of countries and institutions that conducted research on BCT in agriculture, growth trend analysis in research publications, bibliographic coupling of journals using the VOSviewer tool, and the countries and institutions researching BCT.

The authors discovered that China, the USA and India were the highly active countries in BCT research and publication. However, India has only limited research collaboration with other countries as compared to China and the USA. The keyword analysis indicates the role of BCT in order to maintain the transparency of the supply chain by means of protecting the privacy of the personal data of the stakeholders.

More research related to the implementation of BCT in livestock, fishery and agro-forestry sector is recommended.

The case examined is of particular interest as it is concerned with efficient supply chain management.

This study adds value and evidence to the scope and benefits of BCT by providing a comprehensive literature review, with a special focus on the opportunities and challenges concerned with implementation of BCT in the Indian agri-food system.

1. Blockchain technology (BCT) – a promising tool to resolve issues in agriculture supply chain.

2. BCT ensures transparency and protection of information along the supply chain transactions.

3. China, the USA and India are the highly active countries in BCT research and publication.

4. Multiple potential benefits to stakeholders are attributed to the BCT in the agri-food system.

5. The key challenge is to bridge the digital gap between developed and developing nations.

6. Future research on BCT should aim at easing and undistorted competition among stakeholders.

Blockchain technology (BCT) – a promising tool to resolve issues in agriculture supply chain.

BCT ensures transparency and protection of information along the supply chain transactions.

China, the USA and India are the highly active countries in BCT research and publication.

Multiple potential benefits to stakeholders are attributed to the BCT in the agri-food system.

The key challenge is to bridge the digital gap between developed and developing nations.

Future research on BCT should aim at easing and undistorted competition among stakeholders.