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Horse-based tourism stands at the intersection of cultural heritage, leisure activities, and eco-friendly travel, captivating enthusiasts and researchers alike with its diverse facets and impacts. This study examines the horse-based tourism literature to provide an overview of horse-based tourism publications.

Using a systematic literature review (SLR) method, pertinent journal articles published over the past 3 decades were retrieved and analyzed. Based on the review process, 44 papers were identified and analyzed by publication year, journal distribution, research method, and lead author. Using Leximancer software, a thematic analysis was undertaken to determine the major themes of horse-based tourism.

The findings revealed a rising trend of horse-based tourism articles and the appearance of an increasing number of studies in tourism-oriented journals. In addition, it was discovered that the majority of available studies are qualitative, whereas quantitative research is few and limited.

Our research establishes a foundational resource for future studies and scholarly discourse on the multifaceted contributions of horse-based tourism.

This study can assist decision-makers in understanding the potential of horse-based tourism in the sustainable development of destinations. Moreover, it provides clear direction on implementing appropriate strategies to manage horse-based tourism.

This study distinguishes itself as the inaugural comprehensive literature review encompassing the breadth of horse-based tourism publications and research domains. By pioneering this endeavor, we not only contribute a unique perspective to the existing body of knowledge in the field but also emphasize the vital role of horse-based tourism in fostering economic and social sustainability for the countries involved.

Predicting dimensional and geometrical errors in 3D printing parts during the design stage can significantly enhance the product’s quality. This study aims to predict the form deviation and process capability in additive manufacturing (AM) specimens considering layer thickness, laser power and scan speed parameters in the laser powder bed fusion (LPBF) method. Various machine learning (ML) techniques are implemented to estimate the form deviation and process capability with the highest accuracy in 3D-printed cylindrical parts as a case study.

The workflow started by simulating the LPBF AM process using a finite element modeling approach. Then, different ML algorithms like artificial neural networks are used to predict the form deviation. The process capability value is forecasted using some classification ML models and process capability indices (PCIs) for cylindrical parts. Finally, concentricity tolerance classification is performed for cylindrical parts, which can ensure quality control issues in the production stage.

Results present an accuracy of about 93% for predicting form deviations and 95% accuracy for predicting PCI C_pm in PCI classification based on random forest model as an ML algorithm.

The noteworthy point of the research is accessing the form deviation due to AM and process capability evaluation in the AM process before the production stage, which has not been studied before based on the author’s knowledge. So that the product quality is evaluated based on the shape deviation and its tolerances in the AM process digital chain.

The purpose of this study is to analyze the relationship between lean manufacturing and corporate environmental performance. Scholarly literature has extensively addressed the relationship between those two areas but empirical papers present mixed and inconsistent results, calling for further analysis to establish a clearer understanding of the actual relationship and to identify the causes of conflicting findings across studies. Given the importance of sustainable practices in the current business landscape, this paper aims to provide a comprehensive overview of this relationship through a meta-analysis of previous research, with a focus on integrating quantitative findings to shed light on the potential impact of lean manufacturing on environmental performance and report its intensity with Pearson’s correlation coefficient.

This paper analyzes the data from 29 primary studies published between 2001 and 2022 that have empirically measured the relationship between lean manufacturing and corporate environmental performance and that have been identified in the Web of Science and SCOPUS databases through an exhaustive review of the literature. To integrate previous empirical results and evaluate the evidence for the lean manufacturing’s influence on environmental performance, a meta-analytic methodology was adopted through the Hedges–Olkin random effect approach, based on correlations.

Main findings support the notion that a significant, positive, rather moderated, relationship exists between lean manufacturing and environmental performance, with an overall correlation coefficient r¯ = 0.25. The result seems robust, as several tests confirm that publication bias is unlikely. Overall, various lean practices are correlated to varying degrees with different measures of environmental performance. The environmental efficiency of external lean practices is higher than that observed for internal practices and quality management has a more pronounced effect than other internal lean practices. The 2008 global crisis did not change these relationships and the impact of lean manufacturing on environmental performance does not seem to be moderated by the degree of environmental awareness of the country where applied.

The results conclude that a significant, positive relationship exists between lean manufacturing and environmental performance (r¯ = 0.25). This study tests certain factors that exhibit varying effect sizes and moderate the overall outcome, highlighting that the environmental efficiency of external lean practices is higher than that observed for internal practices. In addition, it suggests a more pronounced effect of quality management among other internal lean practices.

This study provides companies with an opportunity to align their operational strategies with environmental sustainability goals. Understanding that various lean practices exhibit diverse levels of correlation with multiple measures of environmental performance, decision-makers can prioritize their efforts and apply the lean practices that have a stronger effect on the desired environmental outcomes to improve their environmental impact. Conversely, managers are aware that certain lean practices have a week relationship with some environmental performance so they can avoid overestimating environmental benefits of lean manufacturing. Finally, results underscore the importance of organizational commitment to environmental sustainability.

It is, to the best of the authors’ knowledge, the first meta-analytic study to investigate the strength of the association between lean manufacturing and environmental performance and to test whether various lean practices are correlated to different measures of environmental performance. It fills this gap in the literature and therefore it represents a valuable contribution to the field. In addition, this paper explores certain factors that moderate the overall outcome.

During the past decade, marketing literature has focused on investigating the dark side of consumer emotions and their behavior. This demands further research for a more in-depth understanding. Hence, drawing on affective events theory, this study aims to examine employee incivility (rude and poor behavior) and its consequences on brand hate. Furthermore, the authors also introduced perceived justice as a moderator to buffer the impact of brand hate.

A scenario-based survey was used to collect data from 212 consumers from the airline industry. Structural equation modeling was performed through SmartPLS.

Findings revealed that employee incivility instigates brand hate. Results further showed that attitudinal brand hate influences brand opposition and detachment, whereas behavioral brand hate only influences brand detachment. Additionally, perceived justice moderates the negative relationship between employee incivility and brand hate. Overall, the results showed that employee incivility can trigger brand hate, and service recovery can reduce the negative impact of employee behavior on brand hate in the aviation sector.

This study contributes to brand hate and service recovery literature.

This study provides deep insights into how employee behavior can cause brand hate and how recovery strategies can help buffer its impact.

In the existing literature, limited studies have focused on organizational factors instigating brand hate. To the best of the authors’ knowledge, this study is the first to associate employee incivility and brand hate.

E-commerce companies employ deceptive techniques known as dark patterns (DPs) to manipulate customer decisions on online platforms. DPs are known to annoy and generate negative emotions in the consumers, which might be detrimental to a brand. Consequently, this study examines the influence of DPs on brand experience (BE) and consumer-based brand equity (CBBE) from the lens of stimulus-organism-response theory in an e-commerce organization.

Survey data was obtained from 419 respondents who frequently make transactions on e-commerce platforms. Subsequently, the authors used partial least squares-based structural equation modeling (PLS-SEM) via the R programming language to analyze the relationships.

It was found that DPs negatively impact the BE and CBBE of an e-commerce firm. Furthermore, BE positively impacts CBBE as well as mediates the relationship between DPs and CBBE. Additionally, no significant moderating influence of shopping frequency was discovered for the relation between DPs and BE.

The study investigates the connection between DPs, BE and CBBE in a general e-commerce context. Results may differ across specialized e-commerce sectors.

The study’s insights could motivate e-commerce managers to reevaluate their use of DPs. The study could help online platforms reorganize their business strategies and adopt a customer-centric approach, which might create a long-term positive relationship with customers. The results might spark discussions over redressing customer relations after previous exploitation via DPs.

To the best of the authors’ knowledge, this study is the first to empirically assess the impact of DPs on crucial brand parameters like BE and CBBE.

This paper has a dual purpose. The first is to provide a thorough analysis of developments in international marketing in relation to the coronavirus disease 2019 (COVID-19) pandemic; the second is to capitalize on these developments to set an agenda for future research in the field of international marketing.

This paper zooms in on and reviews the 18 papers published in International Marketing Review’s (IMR) Special Issue on “Covid 19: advancing international marketing theory and guiding practice” (2023, volume 40, issue 5). It also integrates recent research at the intersection of international marketing and the COVID-19 pandemic.

The paper highlights five areas that embody significant contemporaneous changes brought about by the COVID-19 pandemic and affect international marketing practice. These include (1) shifts in consumer behavior, (2) digitalization and artificial intelligence, (3) disruptions in supply chains, (4) communication and corporate social responsibility (CSR), and (5) international dynamic marketing capabilities. In order to advance international marketing theory in relation to pandemics and other external crises, the paper establishes research directions for each of these areas.

The paper provides a novel and comprehensive categorization of fundamental shifts caused by the COVID-19 pandemic and lays out a research roadmap to advance research in the field of International Marketing (IM). Important implications for practice are also discussed.

The study aims to build upon the Resource-based view of the firm (RBV) and Dynamic Capability Theory (DCT) to perform a meta-analysis on the eco-innovation/SMEs’ sustainable performance relationship.

Employing a psychometric meta-analytic approach with a random-effects model, the study examines a sample of 134,841 SMEs covering 99 studies and 233 study effects. Subgroup and meta-regression analysis were used to test the study`s hypotheses in Comprehensive Meta-Analysis (CMA) statistical software.

Results unveil that the average impact of eco-innovation on SMEs` sustainable performance is positively significant but moderate. Moreover, it was found that eco-process, eco-product, eco-organizational, and eco-marketing innovations positively influence SMEs’ sustainable performance, but the impact of eco-organizational innovation is the strongest. Findings further reveal that eco-innovation positively influences economic, social, and environmental performance, but its effect on social performance is the largest. Moreover, our findings reveal that contextual factors, including industry type, culture, industry intensity, global sustainable competitive index, and human development index, moderate the eco-innovation/SMEs’ sustainable performance relationship. Lastly, methodological factors, namely sampling technique, study type, and publication status, account for study-study variance.

Our findings imply that investing in eco-innovation is worthwhile for SMEs. Therefore, CEOs/managers of SMEs must adopt eco-innovation initiatives by establishing a sustainability vision, developing employee environmental development and training, building a stakeholder management system, and promoting employee engagement in sustainability activities.

The study develops a holistic conceptual framework to consolidate the distinct types of eco-innovation and their association with the sustainable performance of SMEs for the first time in this research stream, thereby resolving the anecdotal results and synthesizing the fragmented literature across culture, discipline, and contexts.

Due to the extreme competition in the e-commerce landscape, online companies resort to driving extra profits by manipulating user decisions via manipulative user interfaces and tricks, known as dark patterns. Although many online users are aware of such manipulative tactics, they struggle to combat dark patterns due to certain challenges. Therefore, this study identifies and ranks the most and least significant user challenges in resisting dark patterns in e-commerce.

Initially, the authors identified 11 user challenges against dark patterns in the existing literature. After collecting expert opinions about the challenges from 17 industry professionals, the authors used grey influence analysis (GINA) to identify the most significant challenges.

The study reveals that lack of user awareness, partial control over cognitive biases and user preference for short-term benefits are the most influential challenges. Conversely, the normalization of aggressive marketing, lack of collective user action and legal challenges were found to have minimal influence.

The study’s findings apply to the generic e-commerce industry and may differ in specialized sectors.

The study’s findings could encourage specialized consumer education regarding dark patterns to assist users in minimizing cognitive biases. Based on the insights, e-commerce companies might differentiate themselves by embracing ethical design methods and supporting consumer trust and transparency above manipulative techniques.

The study pioneered the use of GINA to model user challenges in combating dark patterns, providing fresh insights into how these challenges interact and influence user behavior. It is one of the first to show the cascading effects of user challenges in a manipulative e-commerce environment.

The main fast moving consumer goods (FMCG) retail formats that customers engage with in India are Kirana stores, neighborhood convenience stores (NCS), supermarkets and online retailers. However, there has been less research done on the variables or antecedents that could favorably affect consumers' engagement with these FMCG retail formats. To improve retail practices, this study looks at how female consumers perceive the performance of FMCG retail formats on different antecedents of consumer engagement. The status of consumer engagement with FMCG retail formats was also analyzed.

The present study used exploratory as well as descriptive research design. Previous studies were analyzed to identify the antecedents of consumer engagement. A structured questionnaire was used to collect the primary data from 400 female respondents of two major urban cities in north-western India. The descriptive analysis and one-way ANOVA test were performed to analyze the data.

Kirana stores’ performance on most of the antecedents was not satisfactory. Supermarkets and online retailers performed better on all antecedents. Customer marketing orientation and experiential marketing were the antecedents that required more attention from Kirana stores, NCS and supermarkets. Consumer engagement with online retailers was highest, whereas consumer engagement with Kirana stores was least.

This study offers a comprehensive examination of the antecedents of consumer engagement and consumer engagement with FMCG retail, which no prior research has studied in the context of FMCG retail businesses.

The study examines the impact of various aspects of channel integration quality, personalisation and perceived warmth on behavioural outcomes through customer engagement in omnichannel retailing.

This study is based on the responses of 458 participants, gathered using purposive and snowball sampling methods. PLS-SEM and FIMIX-PLS have been used to examine the heterogeneity in respondents’ views.

The findings emphasise the favourable influence of various facets of omnichannel strategy on customer engagement, which enhances brand affection, leading to stickiness and willingness to pay price premium. Furthermore, identifying three separate customer categories provides detailed insights into how omnichannel aspects appeal to consumer preferences.

The findings underscore the need to use customised approaches to cultivate lasting relationships with consumers, emphasising the potential of omnichannel retailing in harmonising business success and consumer sentiments. Retailers can identify areas of dissatisfaction within specific segments and eventually focus on improving these areas to provide a seamless experience and increase engagement.

This paper offers a distinctive contribution to the domain of omnichannel retailing by employing structural equation modelling (SEM) along with FIMIX-PLS to explore respondent heterogeneity. In addition to the transactional aspects, this study investigates the crucial elements, including warmth and personalisation strategies and how these influence the holistic customer journey, including their emotional connection with the brand in the omnichannel retailing environment, thereby advancing knowledge in the field and providing relevant implications for industry practice.