Purpose: This article aims to clarify the mechanism by which herding behavior influences perceived market efficiency, investment decisions and the performance of individual investors actively trading on the Pakistan Stock Exchange (PSX).Design/methodology/approach: The deductive approach was used in this study, as the research is based on the theoretical framework of behavioral finance. A questionnaire and cross-sectional design were employed to collect data from the sample of 309 investors trading on the PSX. The collected data were analyzed using SPSS and AMOS graphics software. Hypotheses were tested using structural equation modeling (SEM).Findings: The article provides further empirical insights into the relationship between herding behavior and investment management and perceived market efficiency. The results suggest that herding behavior has a markedly negative influence on perceived market efficiency and investment performance, while positively influencing the decision-making of individual investors.Originality/value: The current study is the first to focus on links between herding behavior and investment management activities and perceived market efficiency. This article enhances the understanding of the role that herding behavior plays in investment management and, more importantly, it improves understanding of behavioral aspects and their influence on investment decision-making in an emerging market. It also adds to the literature in the area of behavioral finance, specifically the role of herding behavior in investment management; this field is in its initial stage, even in developed countries, while little work has been done in developing countries.

Purpose: This study aims to explore the mechanism by which intellectual capital and corporate social responsibility (CSR) influence the sustainable competitive performance of small and medium-sized enterprises (SMEs), with the mediating role of organizational innovation in an emerging economy.Design/methodology/approach: The data collection was conducted through a survey completed by 208 owners and top managers operating in the service, trading and manufacturing sector SMEs, positioned within twin cities of Pakistan. Structural equation modeling (SEM) was utilized for data analysis.Findings: The results of the study suggest that intellectual capital and CSR have a markedly positive influence on the sustainable competitive performance of SMEs. The organizational innovation appears to mediate these relationships.Originality/value: This study pioneers research on the links between intellectual capital, CSR organizational innovation and sustainable competitive performance of SMEs. The current research contributes to the literature by defining intellectual capital and CSR as an antecedent and organizational innovation as an intervening variable for the sustainable competitive performance of SMEs. In addition, this study underlines the significance of intellectual capital and CSR activities as valuable intangible assets for the achievement of sustainable competitive performance of SMEs.

Purpose: This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.Design/methodology/approach: For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.Findings: This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.Practical implications: The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.Originality/value: Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

Purpose: This research explores the role of economic growth to influence the inter-relationship between capital, liquidity and profitability of commercial banks in selected asian emerging economies.Design/methodology/approach: To achieve the research purpose, an empirical model was constructed to examine the role of economic growth in the inter-relationship between banks' capital, liquidity and profitability. The empirical model was tested through two stage lease square (2SLS) regression analysis using annual data of Asian commercial banks ranges from 2011 to 2019.Findings: The findings indicate that bank capital and liquidity are interdependent and determined simultaneously. The outcome demonstrates that the strength of the inter-relationship between banks' capital, liquidity, and profitability improves when economic growth is taken into account in the analysis. The results report that market funding, loan ratio, credit risk, bank size and bank efficiency are significant indicators to influence commercial banks' liquidity, profitability and capital in Asian emerging economies. The findings are heterogeneous across large, medium and small-sized banks in emerging economies of Asia.Practical implications: The results highlight that the model provides robust results with respect to sign and significance. However, the coefficient remains underestimated without incorporating economic growth, which has important implications for decision-makers and bankers.Originality/value: To the best of authors’ knowledge, this is the first study that examines the role of economic growth to influence the inter-relationship between capital, liquidity and bank profitability in the emerging economies of Asia.

Purpose: This study investigates the impact of green intellectual capital (IC) on the economic, social, and environmental sustainability performance of manufacturing small- and medium-sized enterprises (SMEs) in Pakistan–an emerging Asian economy–and the mediating effect of sustainable business model innovation (SBMI). It also examines the moderating effect of green dynamic capability (GDC) on the relationship between green IC and SBMI. Design/methodology/approach: Data were collected through a survey completed by 324 owners and top managers of manufacturing SMEs in four Pakistani cities. A purposive and snowball sampling approach was used to gather the data. A dual-stage methodological approach (a combination of PLS-SEM and artificial neural networks) was applied to capture both linear connections and complex, hidden, nonlinear patterns between variables. Regression analysis was used to verify the results. Findings: The findings indicate that green IC positively contributes to manufacturing SMEs' economic sustainability performance (ECSP), social sustainability performance (SSP), and environmental sustainability performance (ESP) in an emerging Asian economy. SBMI appears to mediate these relationships. Furthermore, GDC strengthens green IC's positive effect on SBMI adoption. The artificial neural network results indicate that green human capital has the highest positive influence on ECSP and SSP, suggesting its pivotal role in achieving SMEs' economic and social sustainability goals. However, green relational capital was identified as having the strongest effect on ESP, indicating its crucial role in driving environmental sustainability in SMEs. Originality/value: The present study is a pioneering effort because, to the best of our knowledge, green IC, SBMI, and GDC have never been systematically tested with the ECSP, SSP and ESP of manufacturing SMEs, nor has their predictive ability been analyzed in an emerging Asian economy. Second, this study divulges the mediating role of SBMI in the relationship between green IC and sustainability performance in an emerging market. Third, it adds to the literature by examining the moderating role of GDC in the link between green IC and SBMI and provides valuable insights into how green IC and GDC interact to foster SBMI adoption. Fourth, the study enriches the resource-based view literature by integrating green IC, SBMI, GDC and sustainability performance. Finally, the study is unique in its use of a dual-stage methodological approach consisting of structural equation modeling and artificial neural networks to capture both linear connections and complicated, hidden, nonlinear patterns that conventional statistical approaches might overlook. No study had analytically assessed how the dimensions of green IC affect the ECSP, SSP and ESP of SMEs by employing this hybrid approach so far.