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This paper first aims to examine associations between factors involved in business-to-business complaints management and results (satisfaction and loyalty) and analyses three types of distributors based on their cultural profile (domestic, low context and high context). Second, the paper investigates whether the identified associations remain stable over time.

Data from a sample of distributors for a manufacturing company were gathered during two periods of time. A factorial analysis of correspondences and a cluster analysis were carried out to visually represent the associations among clients, complaints and results in the associations among clients, complaints and results. The stability over time of these relationships was also analysed by calculating the correlations between the Euclidean distances on the two maps (one per year) and their mobility ratio.

The authors found significant evidence that clients from different cultures are associated with varying profiles of complaint and different result types and that certain associations remain stable over time.

While many studies have analysed complaint behaviour in business-to-consumer contexts, there is a lack of research from an international business-business relations point of view, leaving questions virtually unexplored. Second, the last phases of supply chain management, specifically complaints management, have been undeveloped, limiting the cultural factor to the general scope of negotiation. In this vein, this paper compares different complaint profiles and results, comparing culturally different customers/distributors. Third, research has mostly referred to a single period, while this paper investigates two different periods of time for the same company (and their distributors) to analyse the relevance of the stability (or not) over time of the associations identified.

This research explores why tourists are dissatisfied in places considered “wonders of the world”. The authors ask if the place does not match visitors' expectations or if other factors spoil the experience.

The authors analysed the lowest-rated reviews of these wonders on TripAdvisor. The authors identified the main causes of complaints and the problems tourists faced. The authors grouped the complaints into categories and used CoDa.

The results indicate that dissatisfaction does not stem from unmet expectations regarding the monument itself, but rather from other factors related to the quality of the tourist service.

The findings of this research can be implemented in those tourist spots that, despite their global popularity, have considerable proportions of unhappy visitors, not due to the attraction itself, but to shortcomings in its administration.

This study provides a deeper insight into the causes of complaints about some of the most renowned monuments, regarded as extraordinary places, where high satisfaction levels would be anticipated. It also contributes theoretically to the literature on customer complaints in tourist places.

Operation and maintenance (O&M) processes projects such as identification, assessment, planning and execution, embody a variety of standards such as technical (method of statement), environmental, economic (campus development) and social (health and wellbeing). Because these standards have proven to be challenging to integrate, local governments are increasingly experimenting with social innovation (SI) as a bottom-up form of standard integration. This study aims to apply the concept of SI to the O&M processes of facilities management at polytechnics in Malaysia to identify problems with conventional working practices in this area and to recommend potential solutions.

The paper reviews evidence that conventional working methods generate significant problems related to paper-based forms, improper database management and flawed decision-making processes. Because of the lack knowledge about different ways of how standard integration is achieved, the comparison of three polytechnic institutions which are Rensselaer Polytechnic Institute (RPI) and Southern Polytechnic College of Engineering and Engineering Technology (SPCEET) in USA as well as Seberang Perai Polytechnic, Pulau Pinang (PSP) in Malaysia shares the ambition to realise standard integration of O&M through SI.

The findings reveal that SI leads to four ways of standard integration: computerised maintenance management system, online customer complaint, electronic form and relational database. Application of the concept of SI reveals the need for more sophisticated management solutions in the O&M processes of facilities management.

These standard integration arrangements unfortunately seem to mainly contribute to greater alignment between standard rather than true standard integration. The concept of SI will guide future improvements and developments in maintenance management systems to fulfil requirements in this area.

Technology serves as a key catalyst in shaping society and the economy, significantly altering customer dynamics. Through a deep understanding of these evolving behaviors, a service can be tailored to address each customer's unique needs and personality. We introduce a strategy to integrate customer complaints with their personality traits, enabling responses that resonate with the customer’s unique personality.

We propose a strategy to incorporate customer complaints with their personality traits, enabling responses that reflect the customer’s unique personality. Our approach is twofold: firstly, we employ the customer complaints ontology (CCOntology) framework enforced with multi-class classification based on a machine learning algorithm, to classify complaints. Secondly, we leverage the personality measurement platform (PMP), powered by the big five personality model to predict customer’s personalities. We develop the framework for the Indonesian language by extracting tweets containing customer complaints directed towards Indonesia's three biggest e-commerce services.

By mapping customer complaints and their personality type, we can identify specific personality traits associated with customer dissatisfaction. Thus, personalizing how we offer the solution based on specific characteristics.

The research enriches the state-of-the-art personalizing service research based on captured customer behavior. Thus, our research fills the research gap in considering customer personalities. We provide comprehensive insights by aligning customer feedback with corresponding personality traits extracted from social media data. The result is a highly customized response mechanism attuned to individual customer preferences and requirements.

The purpose of this study is to assess the performance of United Arab Emirates (UAE) Government e-services by using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methodology, integrating insights from the balanced scorecard (BSC) framework across financial, customer, internal business and learning and growth perspectives.

Using the fuzzy TOPSIS method, this paper evaluate three e-services in the UAE against 12 criteria representing the balanced scorecard perspectives. Expert evaluation and sensitivity analysis are used to identify the most sustainable e-service alternative.

The study findings emphasize the importance of prioritizing customer-centric metrics, improving service reliability and efficiency, and investing in employee training to enhance e-government service performance in the UAE. Sensitivity analysis reinforces the robustness of our results and identifies key criteria influencing decision-making.

The data was collected only from experts in selected UAE Government departments. This may affect the generalization of the findings. Also, only three e-services were evaluated. Future studies could include various e-services not covered in this study and use different multi-criteria decision-making methods.

Prioritizing customer satisfaction: Priority should be given to customer satisfaction as it is a critical factor in evaluating e-services because of its importance. It also highlights the importance of considering user feedback and ensuring that e-services have a high level of friendliness and responsiveness to their needs. It follows that minimizing errors and ensuring quick and efficient transactions are crucial. Emphasizing reliability and transaction efficiency: Reliable services and transaction efficiency are also essential criteria for evaluating e-government services. This suggests that e-government services should be designed to minimize errors and ensure that transactions are completed quickly and efficiently. Managing IT costs: To deliver e-government services affordably, effective IT cost management is crucial. This emphasizes how crucial it is to effectively manage IT costs to guarantee the efficient delivery of e-government services.

From a customer perspective, adopting BSC can create a favorable customer attitude, encourage long-term customer support, and increase customer satisfaction and loyalty. These factors have significant social implications for UAE and expatriate individuals who are using such e-government services.

This study contributes to the literature by showcasing the applicability of the fuzzy TOPSIS methodology in evaluating UAE e-government service performance. By examining multiple perspectives of the BSC, this paper provide valuable insights into enhancing the efficiency and effectiveness of e-services in the UAE Government sector.

In the context of the journey toward digital transformation and the realization of a fully connected factory, concepts such as data science, artificial intelligence (AI), machine learning (ML) and even predictive models emerge as indispensable pillars. Given the relevance of these topics, the present study focused on the analysis of customer complaint data, employing ML techniques to anticipate complaint accountability. The primary objective was to enhance data accessibility, harnessing the potential of ML models to optimize the complaint handling process and thereby positively contribute to data-driven decision-making. This approach aimed not only to reduce the number of units to be analyzed and customer response time but also to underscore the pressing need for a paradigm shift in quality management. The application of AI techniques sought to enhance not only the efficiency of the complaint handling process and data accessibility but also to demonstrate how the integration of these innovative approaches could profoundly transform the way quality is conceived and managed within organizations.

To conduct this study, real customer complaint data from an automotive company was utilized. Our main objective was to highlight the importance of artificial intelligence (AI) techniques in the context of quality. To achieve this, we adopted a methodology consisting of 10 distinct phases: business analysis and understanding; project plan definition; sample definition; data exploration; data processing and pre-processing; feature selection; acquisition of predictive models; evaluation of the models; presentation of the results; and implementation. This methodology was adapted from data mining methodologies referenced in the literature, taking into account the specific reality of the company under study. This ensured that the obtained results were applicable and replicable across different fields, thereby strengthening the relevance and generalizability of our research findings.

The achieved results not only demonstrated the ability of ML models to predict complaint accountability with an accuracy of 64%, but also underscored the significance of the adopted approach within the context of Quality 4.0 (Q4.0). This study served as a proof of concept in complaint analysis, enabling process automation and the development of a guide applicable across various areas of the company. The successful integration of AI techniques and Q4.0 principles highlighted the pressing need to apply concepts of digitization and artificial intelligence in quality management. Furthermore, it emphasized the critical importance of data, its organization, analysis and availability in driving digital transformation and enhancing operational efficiency across all company domains. In summary, this work not only showcased the advancements achieved through ML application but also emphasized the pivotal role of data and digitization in the ongoing evolution of Quality 4.0.

This study presents a significant contribution by exploring complaint data within the organization, an area lacking investigation in real-world contexts, particularly focusing on practical applications. The development of standardized processes for data handling and the application of predictions for classification models not only demonstrated the viability of this approach but also provided a valuable proof of concept for the company. Most importantly, this work was designed to be replicable in other areas of the factory, serving as a fundamental basis for the company’s data scientists. Until then, limited data access and lack of automation in its treatment and analysis represented significant challenges. In the context of Quality 4.0, this study highlights not only the immediate advantages for decision-making and predicting complaint outcomes but also the long-term benefits, including clearer and standardized processes, data-driven decision-making and improved analysis time. Thus, this study not only underscores the importance of data and the application of AI techniques in the era of quality but also fills a knowledge gap by providing an innovative and replicable approach to complaint analysis within the organization. In terms of originality, this article stands out for addressing an underexplored area and providing a tangible and applicable solution for the company, highlighting the intrinsic value of aligning quality with AI and digitization.

This study aims to test the complaints of tourists who visit five-star hotels in Antalya, Turkey, on those same hotels’ websites.

In the study, the data were collected with qualitative methods but analyzed with the mixed analysis method. In this context, the authors collected 1,012 comments on the website between 2016 and 2019.

According to the results of the study, the most intense complaints were found to be concentrated in categories such as ambience, food and staff.

First of all, it is thought that it will make an important contribution to the literature, since different methodologies are adopted in the study. In addition, online shares, evaluations and comments produce positive or negative results for the destination or business in question. It is necessary to closely monitor such activities in electronic environments, as they may have negative consequences, thus revealing the need to take corrective or preventive measures. For this reason, the research is important in terms of not having such a large-scale study in the literature and contributing to the hospitality industry.

This research addressed online customer-to-customer (C2C) incivility during digital service recovery.

To examine the effectiveness of managerial responses to online C2C incivility post a restaurant service failure, a 2 (Managerial response: general vs specific) x 2 (Failure severity: high vs low) quasi-experimental design was employed. A pretest was conducted with 123 restaurant consumers via Amazon Mechanical Turk, followed by a main study with 174 restaurant consumers. Taking a mixed-method approach, this research first asked open-ended questions to explore how participants perceived the restaurant’s motivation for providing a generic versus a specific response. Hayes’ (2013) PROCESS procedure was then performed for hypotheses testing.

The results revealed significant interaction effects of managerial responses and failure severity on perceived online service climate and revisit intention, mediated by trust with managerial responses.

This research yielded unique insight into C2C incivility management literature and industry practices in the context of digital customer service recovery.

This study aims to identify factors affecting travellers' behavioural intentions regarding beach destinations in Bangladesh. The study also examines how destination experience and satisfaction mediate the nexus between destination service factors and travellers' behavioural intentions.

A self-administered survey was carried out to gather data from 375 people who had visited the beaches in Cox's Bazar. Data were examined using partial least squares structural equation modelling (PLS-SEM) to evaluate the hypotheses.

The destination experience mediates the relationship between destination service factors and complaint intention but does not mediate the relationship between destination service factors and word of mouth (WOM). Moreover, destination satisfaction mediated the relationship between destination service factors and WOM, along with complaint intention.

This study's findings can be utilised by the Bangladeshi destination management to increase the number of tourists by instituting and maintaining improved destination service features in popular tourist destinations.

This is one of few studies on beach tourism destinations in Bangladesh that comprehensively overviews destination service factors and their influence on tourists' behavioural intentions, with a special emphasis on the mediating roles of destination experience and destination satisfaction.

Mining activities can promote development despite issues of environmental and social impact; however, corporate social responsibility (CSR) implementation is still an issue in the industry, which has received little attention in the literature and almost none to the operational level. This paper aims to address this gap by adopting the perspective of CSR practitioners to explore the way mining companies implement CSR at site level.

This paper uses an exploratory approach with in-depth interviews to investigate site-level CSR implementation and challenges in the context of mining in Brazil.

This study identifies primary challenges in CSR implementation and several ways in which they might be addressed. To the best of the authors’ knowledge, this paper identifies for the first time two implementation-hindering aspects of the routine of CSR practitioners – excessive time spent at the office as opposed to in the field engaging in the community and a disproportionate amount of time spent on complaint management. In addition, this paper demonstrates the applicability of stakeholder theory in the CSR field, highlighting the need for increased collaboration among internal and external stakeholders to advance CSR implementation.

This study adopts the perspective of CSR practitioners, who are key stakeholders in CSR implementation, working in mining sites in Brazil, as the impact of mining can be especially marked in developing countries.