Search results

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 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.

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.

Managing project completion within the stipulated time is significant to all firms' sustainability. Especially for software start-up firms, it is of utmost importance. For any schedule variation, these firms must spend 25 to 40 percent of the development cost reworking quality defects. Significantly, the existing literature does not support defect rework opportunities under quality aspects among Indian IT start-ups. The present study aims to fill this niche by proposing a unique mathematical model of the defect rework aligned with the Six Sigma quality approach.

An optimization model was formulated, comprising the two objectives: rework “time” and rework “cost.” A case study was developed in relevance, and for the model solution, we used MATLAB and an elitist, Nondominated Sorting Genetic Algorithm (NSGA-II).

The output of the proposed approach reduced the “time” by 31 percent at a minimum “cost”. The derived “Pareto Optimal” front can be used to estimate the “cost” for a pre-determined rework “time” and vice versa, thus adding value to the existing literature.

This work has deployed a decision tree for defect prediction, but it is often criticized for overfitting. This is one of the limitations of this paper. Apart from this, comparing the predicted defect count with other prediction models hasn’t been attempted. NSGA-II has been applied to solve the optimization problem; however, the optimal results obtained have yet to be compared with other algorithms. Further study is envisaged.

The Pareto front provides an effective visual aid for managers to compare multiple strategies to decide the best possible rework “cost” and “time” for their projects. It is beneficial for cost-sensitive start-ups to estimate the rework “cost” and “time” to negotiate with their customers effectively.

This paper proposes a novel quality management framework under the Six Sigma approach, which integrates optimization of critical metrics. As part of this study, a unique mathematical model of the software defect rework process was developed (combined with the proposed framework) to obtain the optimal solution for the perennial problem of schedule slippage in the rework process of software development.

Studies on the negative aspects of consumer–brand relationships have received increasing attention in academia, but most research on this phenomenon is not focused on services. On the other hand, the literature consistently demonstrates evidence that gender affects consumer behavior. In this context, this study aims to unprecedentedly identify the antecedents of brand hate and the effects of consumer gender across different service sectors.

This research compares the results of two studies with service companies. The first was accomplished with 307 consumers of mobile phone operators, and the second study was performed on 450 higher education students. The data were analyzed using structural equation modeling.

In both studies, females showed greater importance for ideological incompatibility than males. This suggests that females are more sensitive to moral issues and ethical behavior than males. As for males, negative experience is the most relevant antecedent of brand hate in both samples. However, when age is checked, the results indicate that younger males develop more brand hate than older males. This does not happen with females.

This study demonstrates gender differences and compares two samples applied in different service sectors: low-technological and high-touch consumer interactions. The results show that the antecedents of brand hate for males and females in the service sector differ. This study also points out that older males present a different behavior when compared to younger males, which does not happen with females.

In today’s fast-paced and interconnected market, companies must adapt to the evolving demands of their customers. Therefore, it is essential to examine the impact of online reviews on potential customers' intent to purchase. This study seeks to identify the characteristics of electronic word-of-mouth (eWOM) that influence a buyer’s intention to purchase goods and services.

We used the snowball sampling method to collect data using a pre-tested survey instrument with a five-point Likert scale. We received 696 usable responses. We conducted assumption tests to ensure that we could use covariance-based structural equation modelling (CB-SEM) for data analysis. The collected data were analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to compute the latent variables. We then tested our research hypotheses using CB-SEM.

Eight latent constructs – perceived persuasion, perceived information, image aesthetics, ease_of_experience, eWOM_credibility, eWOM_usefulness and eWOM_adoption – have been identified, which determine the influence of eWOM on purchase intent (PI) for both tangible and experiential products. Though the structural model emerged relatively similar, the constructs had differential impacts on PI for commodities and services. The perceived information quality and source trustworthiness had a greater impact on eWOM credibility in the case of services than in the case of commodities, while image aesthetics played a more crucial role in determining the eWOM credibility for commodities than services. In both cases, credible eWOM was found useful, but a persuasive eWOM influenced its perceived usefulness more in the case of commodities. The likelihood of adopting a useful eWOM and converting it to positive PI is present in the case of both services and commodities, but the impact is much higher in the case of services.

The study has examined the interplay of three theoretical consumer behaviour models: elaboration likelihood model (ELM), stimulus-organism-response model (SOR), and information adoption model (IAM). Thus, it adds to the existing literature on the characteristics of eWOM that influence the PI of online buyers.

This study’s findings demonstrate how eWOM influences consumers' perceptions of the utility of goods and services, impacting their intention to purchase. It also provides valuable insights into marketing and consumer behaviour in the Indian market. Thus, this study assists marketers in adjusting their digital marketing strategies to ensure the effective use of eWOM characteristics to positively influence the PI of the target audience in the Indian market.

This research study examines the relationship between eWOM characteristics and PI for both goods and services sectors. Most existing literature is skewed towards specific service sectors, such as hospitality and health care. A generalised comparative study is what makes this research work unique.

This study aims to investigate the experiences of frontline managers supervising and developing staff to support autistic adults living in two types of residential housing in the community.

A qualitative approach used semi-structured interviews with 14 frontline managers. Audio-taped material was transcribed and analysed using thematic analysis.

Two main themes emerged. Theme 1 “autism in practice” illustrates commonalities observed to affect autistic adults with learning disabilities receiving staff support; whilst one sub-theme illustrated the diversity in how these commonalities may be experienced and expressed, another focused on participants’ experiences of staff concerns regarding behaviours described as challenging. Theme two, “what’s important in autism-informed support” reflected participants’ perceptions of the features of successful person-centred staff support for autistic service users.

The “rich” experiences of these managers may not be readily generalised.

Features of good staff support for autistic adults who may show behaviours of concern included attending to individuals’ specific communication and sensory needs and for predictability within their environments. Developing staff skills and confidence to implement skilled approaches in the context of often high risk behaviour of concern took time and frontline managers “on site” to observe, coach, mentor and demonstrate good practice. More intellectually (verbally) able service-users were perceived as more “difficult” to support.

Staff supporting autistic adults in ordinary housing need frontline managers to act as practice leaders rather than administrators.

This study is the first to report, to the best of the authors’ knowledge, on management for staff supporting autistic adults living in community housing.

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.