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This paper compares traditional and digital banks in nine categories of complaints and provides insights to improve complaint management performance.

A sample of the major Brazilian banks was defined, with four traditional and four digital banks. The grey relational analysis (GRA) method was applied as an analytical tool to compare the most frequent complaints of traditional and digital banks. The most critical complaints identified were considered to discuss potential improvements in complaint management using quality and service management system concepts.

The GRA method enabled the development of a ranking of nine complaint categories, considering the uncertainty involved in the data and differentiating between traditional and digital banks. The most critical complaint categories, regardless of business model, were “unauthorized charges” and “poor service,” which were ranked first and second in the frequency rankings. Traditional and digital banks differed the most in the complaint category “unfair charge,” ranking third and eighth in the rankings, respectively.

Managers from traditional and digital banks can improve complaint management performance by applying ISO 9001 and ISO 20000 concepts such as incident, problem, change, service level, availability, capacity, information technology service continuity and financial management.

The study's findings can help bank managers improve service levels in the face of technological competition. Improving these organizations is an important factor for developing countries such as Brazil.

This paper reveals the differences between two business models regarding complaint management. It also considers a methodological approach to include the uncertainty related to customers' perception and subjectivity inherent to complaints.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.

The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.

(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.

The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.

The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.

This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

This study aims to articulate the conceptual foundations of the role of accounting infrastructure (calculative practice and the communicative dimension of accounting) in extractive industries (EIs) towards a sustainable orientation from an actor-network theory (ANT) perspective.

This study is a literature-based analysis of the calculative property and communicative dimension of accounting in EIs, using the concepts of calculability, assemblage and other related concepts from ANT to identify potentialities and limits of the roles of accounting in this sector.

While accounting infrastructure can influence social and environmental outcomes, it has not, as yet, led to ecologically and socially sustainable practices in EIs. Calculative properties and the communicative dimension of accounting infrastructure have capabilities to foster the phenomenon of “sustainability” in EIs by valuing, disclosing (reporting) and governing EIs towards a sustainable orientation. Conceptualizing sustainable EIs as a promissory economy, accounting infrastructure serves as a tool not only to represent past performance but also to enact the future: it helps to shape a sustainable future for the industry by informing and triggering behavioural decisions of EIs firms towards sustainable practices.

This conceptual paper is anticipated to stimulate future sustainability accounting research. The research agenda discussed in this paper can be used to enrich our understanding of the role of accounting in sustainability.

This paper charts a direction for future research by interpreting the role of sustainability accounting within networks of sociotechnical relations, using ANT concepts which attach importance to the dualism of nature and society. Conceptualizing sustainability accounting and reporting as an infrastructure, which draws more attention to the relationality characteristic of accounting, the study goes beyond the traditional interpretation of accounting as a mediation device and draws on a contemporary view of accounting by invoking the dynamic relation between accounting and society, in the context of EIs.

An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s needs throughout the service journey. This article envisions the idea of AI concierges and discusses how to leverage AI concierges in the customer journey.

This article takes a conceptual approach and draws insights from literature in service management, marketing, psychology, human-computer interaction and ethics.

This article delineates the fundamental forms of AI concierges: dialog interface (no embodiment), virtual avatar (embodiment in the virtual world), holographic projection (projection in the physical world) and tangible service robot (embodiment in the physical world). Key attributes of AI concierges are the ability to exhibit semantic understanding of auditory and visual inputs, maintain an emotional connection with the customer, demonstrate proactivity in refining the customer’s experience and ensure omnipresence through continuous availability in various forms to attend to service throughout the customer journey. Furthermore, the article explores the multifaceted roles that AI concierges can play across the pre-encounter, encounter and post-encounter stages of the customer journey and explores the opportunities and challenges associated with AI concierges.

This paper provides insights for professionals in hospitality, retail, travel, and healthcare on leveraging AI concierges to enhance the customer experience. By broadening AI concierge services, organizations can deliver personalized assistance and refined services across the entire customer journey.

This article is the first to introduce the concept of the AI concierge. It offers a novel perspective by defining AI concierges’ fundamental forms, key attributes and exploring their diverse roles in the customer journey. Additionally, it lays out a research agenda aimed at further advancing this domain.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.

The initial observation of this study is the gap of research in the economic application of data spaces in wholesale. With the lowering threshold in using digital technology in innovative services wholesale is confronted with new competition in their main business – the purchase and sale of products in large numbers. Wholesale must advance in their own business creating new digital services for their customers to stay relevant competitors in their markets.

The design follows an explorative, heuristic and interdisciplinary approach (social sciences and in-formation systems) of a multiple case study combining semi-structured, open and participating observation in three case studies. The cases were set in tourism, construction, as well as manufacturing and were each scientifically accompanied for more than one year during the identification of implementation of strategies for data spaces as digital entrepreneurial path.

The study shows four strategies in the implementation of data spaces in traditional wholesale. These data spaces have their focus in (1) the traded commodity with two specificities (1a and 1b), (2) the customer and (3) the cooperation of an ecosystem of companies. Each have their own challenges, chances and specifications like the data sovereignty. These strategies are embedded in the behavior of digital entrepreneurship.

This study accompanied and observed the entrepreneurial strategies of three wholesalers discovering new opportunities enabled via data spaces. These three strategies follow different approaches offering potentials for other wholesalers.

The aim of this paper is to study the effect of strategic and project related potential risks on project delivery in Qatar. Two objectives have been defined. The first is to identify potential risk indicators (manifest variables) and categorize them (constructs/latent variables) based on a literature review, while the second is to examine and rank the relationships between the indicators and constructs by developing a structural equation model.

Twenty-five indicators were identified from the literature review and categorized into five groups. To collect the data, an online questionnaire was distributed in Qatar, and 116 responses were obtained. Structural equation modeling (SEM) was used to examine the model. The model that was developed based on the research hypothesis met goodness-of-fit, reliability and validity requirements.

The results showed that all constructs contributed well to the model and that the project parties (PPs) have the highest contribution with an effect weight of 0.209 followed by economic and legal (EL) conditions with an effect weight of 0.205. Site and safety (SS) conditions were third with an effect weight of 0.200 while environmental, natural and technological (ENT) conditions were fourth with an effect weight of 0.1989. The last ranked construct is political and social (PS) conditions with an effect weight of 0.186. Based on the outcome of the SEM, recommendations were provided to industry professionals in Qatar about mitigating the impact of potential risks on construction project.

To the authors' best knowledge, this is the first study to quantify the effects of strategic and project related risks on a construction project using SEM, considering the risk management indicators of SS, EL, ENT, PS in Qatar. The study's practical implications are to enlarge the project's risk management plan by considering the strategic and project related risks to enhance the project performance for the cost overrun and delay. The study is intended for construction projects in Qatar, but it can easily be adapted to other parts of the world given the local circumstances.

The purpose of this study is to identify the norms that underlie and condition the decisions made by preparers of financial reports.

This interview-based study illustrates how financial report preparers engage in behaviors linked to the perception of recognition and measurement of internally generated intangible assets by important stakeholders. All of the companies included in the study adhere to International Financial Reporting Standards when creating their consolidated financial statements. The participants selected for the study are involved in accounting decisions related to research and development in accordance with International Accounting Standard (IAS) 38.

The authors identify the normative assumptions underlying the recognition and measurement of internally generated intangibles, which are based on concerns of consistency, credibility and reasonableness. The authors find that the normative basis for legitimacy in financial accounting is primarily related to cognitive legitimacy and is not of a moral or pragmatic nature.

The study reveals that recognition and measurement of internally generated intangibles in financial accounting relate to legitimacy. The authors identify specific norms that form the basis of this legitimacy, namely, consistency, credibility and reasonableness. These identified norms serve as constraints, mitigating the risk of judgment misuse within the IAS 38 framework for earnings management.