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Despite various consequences for different stakeholders in the mustard ecosystem, India prohibited blending in mustard oil to achieve self-reliance in edible oils and promote consumer health. This paper uncovers the implications of this policy on mustard production, consumption and prices.

This paper deploys system dynamics (SD) to model the mustard ecosystem. SD uses simulation modeling to comprehend the nonlinear behavior of complex systems over time utilizing causal-loop and stock-flow diagrams.

While the mustard price does not vary in the short run, it diverges toward a higher side in the long run due to the changed policy mandate. Surprisingly, due to the predominance of market prices, the policy administered minimum support price (MSP) was found to have a limited influence on mustard prices. Hence, the focus should be on supply augmentation through non-price-based measures like disseminating information to enhance the yield rate of seed production and promoting the adoption of efficient technologies with higher oil conversion efficiency.

The paper allows policymakers to quantitatively evaluate the effectiveness of policy interventions to mitigate the adverse impacts of policy mandate. It presents a reliable roadmap for policymakers to roll out effective policies.

The paper uncovers the system-level impact of policy on stakeholders and examines the effectiveness of MSP.

This study aims to investigate the effects of environmental, social and governance (ESG) performance on financial risk disclosure of European companies. It analyzed the relationships between ESG factors and financial risk disclosure between 2010 and 2020.

To test their hypotheses in this study, the authors used the multivariate regression analysis on panel data using the Thomson Reuters ASSET4 database and the annual reports of 154 European companies listed in the ESG index between 2010 and 2020.

Empirical evidence shows a positive association between European companies' environmental and governance performance with financial risk disclosure, whereas social performance does not influence financial risk disclosure. Concerning the control variables, the findings demonstrate that firm size and profitability are significant factors in changing the financial risk disclosure. Nevertheless, firms’ leverage is insignificantly correlated with financial risk disclosure.

This study extends the stream of accounting literature by focusing on the financial risk disclosure, a topic that has received little attention in previous research. Furthermore, to the best of the authors’ knowledge, this study is one of the first that provides ESG companies with evidence of the effect of ESG factors on financial risk disclosure in a developed market like Europe.

Deposits, a liability component of banks’ balance sheet, are an important source of funding for commercial and retail banks. In this study, the authors consider deposits as dependent variable and examine factors (bank-specific, macrofinance and structural) that could plausibly explain deposits. Subsequently, the findings are expected to support analysts, bank managers and regulators, especially in small economies such as Fiji, for asset–liability management.

This study uses a balanced panel of six commercial banks and two credit institutions over the period 2000–2022. To control for bank heterogeneity, a fixed-effect regression method is used.

Bank-specific variables such as bank size, profitability, loan-to-deposit ratio and bank stability are positively associated with bank deposits, whereas the capital adequacy ratio is negatively associated with bank deposits. Macroeconomic variables such as remittances and gross domestic product per capita are positively associated with bank deposits. Moreover, institutional variables such as control of corruption, political stability and regulatory quality are positively associated with bank deposits. However, tail events such as the global financial crisis of 2007–09 and the COVID-19 pandemic negatively influence bank deposits. Structural breaks for 2007 and 2011 of two banks (Bank of the Baroda and Bank of the South Pacific, respectively) are positively associated with bank deposits.

Previous studies have considered profitability, competition, nonperforming loans and stability of banks in Fiji. To the best of the authors’ knowledge, this study is the first to consider the determinants of bank deposits, an important source of funds for banks in many small countries including Fiji. In addition, this study examines the impact of structural breaks, tail events such as the recent pandemic (COVID-19) and institutional variables.

This paper examines and compares the role of social protection to promote inclusive growth in two countries (once related), Pakistan and Bangladesh, from 1984 to 2020, using annual time series data.

The study used principal component analysis to develop the index of social protection, inclusive growth and macroeconomic stability. It also employed co-integration with impulse response function and fully modified ordinary least squares test for long-run cointegration.

The key results highlighted that social protection positively promotes inclusive growth in both countries. However, Bangladesh attains a high position in achieving inclusive growth through the mechanism of welfare programs. Findings show that institutional quality, macroeconomic stability and globalization are the positive and significant drivers of inclusive growth in both countries. It also confirms that macroeconomic stability and globalization are contributing more to achieving inclusive growth in Bangladesh as compared to Pakistan.

Institutions and macroeconomic stability in both countries are critical toward providing a transparent system of welfare schemes to achieve inclusive growth. Shocks to social protection schemes in Pakistan are inconsistent for achieving inclusive growth as compared to Bangladesh.

The study extends the empirical measurement of social protection and inclusive growth while using protracted dimensions and indicators. It further examines and compares the dynamics of social protection programs for inclusive growth in two countries once related. For further originality and reliability, this study checks the robustness of long-run estimates by disaggregating the institutional quality and globalization into their key dimensions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0548

This study addresses the ever-increasing cyber risks confronting the global banking sector, particularly in India, amid rapid technological advancements. The purpose of this study is to de velop an innovative cyber fraud (CF) response system that effectively controls cyber threats, prioritizes fraud, detects early warning signs (EWS) and suggests mitigation measures.

The methodology involves a detailed literature review on fraud identification, assessment methods, prevention techniques and a theoretical model for fraud prevention. Machine learning-based data analysis, using self-organizing maps, is used to assess the severity of CF dynamically and in real-time.

Findings reveal the multifaceted nature of CF, emphasizing the need for tailored control measures and a shift from reactive to proactive mitigation. The study introduces a paradigm shift by viewing each CF as a unique “fraud event,” incorporating EWS as a proactive intervention. This innovative approach distinguishes the study, allowing for the efficient prioritization of CFs.

The practical implications of such a study lie in its potential to enhance the banking sector’s resilience to cyber threats, safeguarding stability, reputation and overall risk management.

The originality stems from proposing a comprehensive framework that combines machine learning, EWS and a proactive mitigation model, addressing critical gaps in existing cyber security systems.

This study aims to investigate the nuances of celebrity spokesperson effectiveness in business-to-business (B2B) advertising. Specifically, the study addresses the question of endorser effectiveness in the presence of product complexity (high vs low) and how this effect is moderated by endorser gender. In addition, the study also explores whether the way an endorser is placed in the advertisement (product-facing vs audience-facing) would have differential effects on the buyer.

The present study uses experimental design to fulfil the study objectives. Two experiments are conducted (total n = 201) on employees in a purchasing role in organisations, with the dependent variable being dwell time (captured using an eye-tracking device).

Major findings indicate that celebrity gender has a moderating effect depending on the product complexity. Results also indicate a significant effect of how the celebrity is placed in the advertisement on the buyer.

The findings emphasise the role of the spokesperson in B2B advertising using neuro-behavioural data. It also contributes to the theoretical nuances of spokesperson gender in B2B advertising and the role of kinesics in advertising using spokespersons.

The study provides guidelines on the choice of the spokesperson and their physical posture in the advertisement for B2B advertisers that may lead to communication effectiveness.

The present study is in a domain that is scarcely researched in B2B and adds novelty as it uses physiological data instead of self-reported measures.

This study aims to investigate how chatbots’ warmth and competence affect customer behavioural expectation (i.e. purchase, recommendation) through perceived humanness and perceived persuasiveness. Moreover, prior knowledge of chatbot is considered the boundary condition of the effects of chatbots’ warmth and competence.

A lab-in-field experiment with 213 participants and a scenario-based experiment of 186 participants were used to test the model using partial least squares structural equation modelling via SmartPLS 4.

Chatbot warmth positively affects customer behavioural expectation through perceived humanness while chatbot competence positively affects customer behavioural expectation through perceived persuasiveness. Prior knowledge of chatbot positively moderates the effect of chatbot warmth on perceived humanness.

This study provides nuanced insights into the effects of chatbots’ warmth and competence on customer behavioural expectation. Future studies could extend the model by exploring additional boundary conditions of the effects of chatbots’ warmth and competence in different generations.

This study offers insightful suggestions for marketing managers on how to impress and convert online customers through designing verbal scripts in customer−chatbot conversations that encourage the customers to anthropomorphise the chatbots.

This study probes into the effects of chatbots’ warmth and competence on customer behavioural expectation by proposing and examining a novel research model that incorporates perceived humanness and perceived persuasiveness as the explanatory mechanisms and prior knowledge of chatbot as the boundary condition.

Despite IoT’s huge potential, enterprises’ ability to leverage it is their competitive advantage. Thus, competitive differentiation is primarily predicated on leveraging IoT toward customer needs. To examine the research gap, this study aims to explore the drivers of customer satisfaction and how they are affected by the interaction between IoT capabilities.

A mixed-method research framework is applied to assess the impact of IoT capabilities on customer satisfaction. Based on the theoretical underpinning of the resource-based view and dynamic capability, the study highlights the importance of IoT capabilities in active resource allocation and effective resource utilization. First, DEMATEL is used capture the interrelationship between IoT capabilities. Further, the impact of each IoT capabilities on customer satisfaction is studied using CoCoSo method.

The study highlights the importance of IoT capabilities in active resource allocation and effective resource utilization. The findings are enriched through the complementarity of resources in a dynamic business-to-business-to-customer (B2B2C) scenario. The authors expand the IoT capabilities from conventional business-to-business (B2B) or business-to-customer (B2C) scenario to tri-nodal B2B2C relationship triangle.

Based on the findings, the authors offer a business transformation strategy for firms in key areas of customer satisfaction by leveraging IoT. The study can help management prioritize and develop key IoT capabilities to meaningfully increase customer satisfaction metrics.

Building on the dynamic capabilities and resource-based view of the firm, an integrated decision-making research model is proposed. In addition, this study investigates the product and service capabilities unlocked using IoT capabilities. This work can be considered one of the leading attempts to improve customer satisfaction using IoT capabilities from traditional dyadic (B2B or B2C) structure to triadic (B2B2C) framework.

A significant increase in the number of private sector banks has intensified the level of competition in the Indian banking industry (IBI). This increase in the number of banks has a considerable impact on the existing players, which calls for prioritizing customer satisfaction (CS) and enhancing bank reputation (BR). Our study seeks to investigate the enablers of CS and BR in the IBI.

The study adopted a cross-sectional design for gathering responses from retail bank customers across the selected banks through a structured questionnaire. Structural equation modeling (SEM) was utilized to evaluate direct and indirect linkages among the identified constructs by examining mediating and moderating effects.

The study puts forward crucial antecedents of CS and BR. The findings exhibit that perceived trust (PT) and relationship commitment (RC) magnify CS and BR, respectively, while CS amplifies repurchase intention (RI). The study advances that BR and CS partially mediate between the underlying constructs. In addition, fairness and risk exhibit moderating effects between CS and customer repurchase intention (CRI) and BR and CRI.

The study illustrates the crucial enablers of BR, CS and CRI that may assist banking professionals in enriching customer experience and holding on to their customers.

There is a shortage of research on RC, service innovation (SI) and BR in the IBI. Accordingly, our study builds on the prior studies by considering these constructs using a comprehensive conceptual framework by extending the application of signaling theory (ST) in the banking domain and scrutinizing the dual moderating effects of fairness and risk.

This study aims to explore the influence of perceived value, enjoyment and novelty of fast-food chains’ smart retailing technology (SRT) on Filipino consumers’ attitude and loyalty.

Purposive sampling was used in identifying the respondents (N = 343). The participants were composed of consumers of the leading fast-food chains in the Philippines, where SRT using self-service ordering kiosks is being implemented. The hypotheses were explored using partial least squares path modeling, and predictive-causal was the study’s research design.

The results reveal that, among the factors, perceived enjoyment substantially contributes to the formation of favorable consumers’ attitude toward SRT. Moreover, perceived value was found to have a moderate effect on attitude while perceived novelty showed small impact. In terms of consumers’ attitude and loyalty, the two variables were found to have large positive and significant relationship. The moderation analysis shows that consumers’ attitude toward SRT has medium indirect effect on the relationship between perceived enjoyment and loyalty, while there is small indirect influence on the links between perceived value and loyalty, and between perceived novelty and loyalty.

As more and more fast-food establishments are adopting the use of SRT via self-ordering kiosks, the present study is the only study in the Philippine context that explores how perceived value, enjoyment and novelty affect consumers’ attitude and loyalty.