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Based on the stimuli-organism-response model and relationship marketing theory, the effect of different dimensions of Servicescape (Ambience, Cleanliness, Functionality, Spatial Layout, Employee Service Quality) on Customer Satisfaction and Behavioral Intention in hospitals during the COVID-19 pandemic are considered.

The study takes a quantitative approach, applying structural equation model using partial least square structural equation modeling to test the hypotheses. A total of 360 responses were collected using questionnaires distributed to different individuals who visited private hospitals in the past two months in India.

Contradicting previous research, this study found that among servicescape dimensions, employee service quality had the maximum influence on customer satisfaction and cleanliness does not have any significant impact on customer satisfaction as hypothesized. Mediation results show that customer satisfaction has a partial mediation effect for all servicescape dimensions except ambience, as both direct and indirect effects are significant. Importance-performance map analysis was performed on the responses collected, and it was found that employee service quality is the most important dimension affecting servicescape, followed by functionality and spatial layout. Thus, health-care institutions should focus on these factors to keep their customers satisfied.

Past studies have focused on the roles of servicescape and customer satisfaction separately. The authors have extended the literature by examining the combined effects of both servicescape and customer satisfaction. The findings from the study, therefore, help in developing a deeper understanding of the literature on the behavior intention relationship in the context of health care, as well as in service marketing.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

The purpose of this study is to examine the impact of firm environmental, social and governance (ESG) rating scores on market perception and stock behavior from 2017 to 2021 while controlling for COVID-19 severity score.

The authors used panel regression models with robust standard errors based on cross-country and cross-industry sample of 1,324 ESG firms from 25 emerging countries across four regions. Four separate regression analyses are used. Hausman test is used to determine whether fixed-effect (FE) or random-effect approaches should be used in regression models. Lagrange multiplier test is used to test for time FEs, and F-test for individual effects to choose between pooled ordinary least squares model and FE. Two-unit root tests are conducted to check stationarity. Heteroskedasticity and serial correlation were controlled through a robust covariance matrix estimation.

The authors provide evidence that the stakeholder theory persists in emerging countries. Overall, the results suggest that firms’ stock behavior is positively associated with the level of environmental and social performance in the region. However, the results do not provide empirical evidence to support the link between ESG performance and stock market perception proxied by the price-to-sales ratio. The results suggest that Refinitiv and Bloomberg ESG rating scores have a positive impact on stock performance in emerging markets, albeit the Bloomberg rating score is insignificant.

Favorable impact of environmental and social performance on stock performance suggests that policymakers should take initiatives to raise awareness toward investments in ESG projects. Evidence shows that ESG stock performance in emerging markets does not insulate firms from the COVID-19 severity. Furthermore, this study highlights the inconsistency in calculating the ESG ratings, therefore, a more standardized approach is recommended to support investors seeking sustainable investments.

The findings have social implications for investors with proenvironmental preferences and nonpecuniary motives for ethical investments. Asset fund managers should develop ESG investment strategies to promote investor preferences that are linked to the proenvironmental and prosocial attitudes by increasing their investments in stocks of firms that behave ethically and support the environment. Furthermore, the findings show that investors pay a price for ethical and socially responsible investments as they are evaluating the environmental and social activities, hence, the firm ESG profile influences equity valuation and risk assessment.

The study extends the literature and provides evidence from the unique setting of emerging markets by analyzing the relationship between ESG rating scores and the COVID-19 severity scores on one hand, and stock behavior and market perception on the other.

This paper reviews the literature on disability inclusion (DI) in supply and demand chains of hospitality and tourism (H&T) organisations. The purpose of this study is to assess disability support and interventions within H&T organisations. Through the assessment, we identified gaps to recommend H&T scholars’ and practitioners’ knowledge of DI from new perspectives.

An integrative review was conducted to examine the published evidence on DI in H&T organisations. This study used high-ranking H&T journals from the Scopus and Web of Science databases between 2001 and 2023. In total, 101 empirical papers met the criteria for the review analysis.

DI focuses heavily on customer disabilities, with scant research on DI in H&T employment. The review emphasises the critical need for empirical research into the varied disability employment ecosystem within H&T organisations, focusing on social integration for inclusive workplaces.

This study contributes to the H&T literature, which previously overlooked the disability context in diversity. The research offers strategies for creating inclusive environments in the H&T industry for disabled consumers and producers.

This study aims to guide firms in emerging markets on whether corporate social responsibility (CSR) engagement facilitates their access to debt with the moderation of asset structure and firm performance. Considering the moderating effect analysis, this study explores the substitutive or complementary effect of these two contingencies on CSR-oriented firms in accessing debt financing.

Drawing on data collected for 16 emerging markets between 2008 and 2019, this study runs country–industry–year fixed-effects regression.

This study finds that CSR performance and reporting facilitate access to debt in emerging markets. However, CSR performance does not have an inverted U-shaped influence on firms’ access to debt financing. The moderation analysis of this study shows that asset tangibility has a negative moderating effect on the link between CSR engagements (i.e. both CSR performance and reporting) and access to debt, confirming a substitutive relationship between asset tangibility and CSR engagements in accessing debt. In contrast, firm performance is positively moderating the nexus between CSR engagement proxies and access to debt, which confirms a complementary type of relationship between firm performance and CSR engagements in accessing debt.

The empirical evidence of this study implies that creditors critically consider CSR engagements of firms in the loan-granting decision process. Similarly, the inverted U-shaped relationship between CSR and access to debt implies that there is an optimal level of CSR engagement creditors might consider in their decision. Likewise, the moderating effects analysis highlights that asset tangibility and firm performance are two conditions under which CSR performance and reporting are linked to access to debt.

Emerging countries are a different set of countries than developed ones; they have high growth rates and hence need financing, have a weaker institutional environment and have weaker stakeholder power. These particularities motivated the authors to conduct a separate study focusing on CSR and debt financing links drawing on a wide range of emerging countries. Thus, this study adds to the ongoing debate by examining the conditions under which CSR-oriented firms can access debt financing in emerging economies.

Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

This study aims to explore how females on committees (FOC) and committee ethnic diversity (CED) impact environmental, social and governance performance (ESGP).

This study examines 126 listed firms under the coverage of FTSE ESG Ratings in Bursa Malaysia between 2017 and 2019. This study applies partial least squares structural equation modeling (PLS-SEM) to examine the hypotheses. While the risk of common method variance is minimised using multiple data sources for the analysis, instrumental variable-free approach, i.e. Gaussian copula method which is implemented in SmartPLS 4.0 has been used to address the potential endogeneity of the model.

Empirical evidence demonstrates significant positive direct relationships between FOC and ESGP, as well as CED and ESGP. The argument of resource dependence theory and positive empirical results on the two direct relationships hold firm despite several committees being aggregated as one construct with the aim of providing different insights into the literature.

This study provides implications for firm leadership to consider reviewing the composition of committees by increasing female representation while striking a balance in the appointment of committee members of different ethnicities to enhance firm ESGP.

To the best of the author’s knowledge, this study adopts a holistic approach by capturing, for the first time, the female representation of audit, nomination, remuneration and risk management committees. These dimensions are further developed into a single quantifiable variable, presented as FOC. Similarly, the ethnic diversity of the respective committees is aggregated and developed into a single quantifiable construct: the CED. Unlike most existing studies that commonly use econometric software, the application of PLS-SEM in this study contributes to the limited body of corporate governance and ESG studies that use PLS-SEM.

The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.