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Augmented reality (AR) technology presents novel opportunities for marketers to captivate consumers, enhancing their experiences with brands. Although recent research underscores consumers' favorable responses to AR within retail contexts, there remains a paucity of studies examining the specific factors motivating these responses, i.e. reasons for, such as the appeal of entertainment, trendiness, customization, interaction and augmentation quality. Conversely, reasons against AR acceptance, such as perceived lack of realism, skepticism or perceived deception, are also underexplored.

Guided by the behavioral reasoning theory, the current study delves into consumers' personal values and beliefs, their reasons for and reasons against using AR apps and how these factors influence their engagement and relationship performance with AR apps. The data were collected from 343 AR app users to test the developed theoretical framework.

Results reveal that while perceived value compatibility does not influence reasons for using AR apps, it negatively influences reasons against using AR apps and positively influences connectedness to AR apps. Interestingly, openness to change does not significantly influence users’ connection to AR apps, and no association was found between reasons-against and connectedness to AR apps and relationship performance. However, a positive relationship was observed between users’ connectedness to AR apps and their relationship performance.

By offering these insights, this study contributes to a foundational understanding of the behavioral intricacies and dynamic interaction patterns within the rapidly emerging AR user base.

The purpose of this paper is to examine the impact of trade openness on the cost of financial intermediation and bank performance. Developed and developing countries are currently pursuing trade openness to achieve higher bank performance with less intermediation costs.

In attaining the study's objectives, several regression methodologies were employed (i.e. system generalized method of moments (GMM), fixed effect, pooled ordinary least squares (OLS) and vector error correction model (VECM)). The authors tested the hypothesis on data of 885 banks from BRICS countries, which span 18 years (2000–2017).

The results from this robust study showed that embedding higher trade openness reduces financial intermediation costs and improves banks' performance. The results remain robust following the use of different estimation methods and alternative variables as proxies. In addition, results were still valid upon considering bank level, industry level and country level as control variables. It was also observed that the relation pattern holds its rigidity during “good” and “bad” times (i.e. the global financial crisis).

The results provide better references for bank regulators, academics and policymakers to take advantage of the low financial intermediation costs resulting from trade openness.

This is mainly because the restrictive condition of intuitionistic hesitant fuzzy number (IHFN) is relaxed by the membership functions of Pythagorean probabilistic hesitant fuzzy number (PyPHFN), so the range of domain value of PyPHFN is greatly expanded. The paper aims to develop a novel decision-making technique based on aggregation operators under PyPHFNs. For this, the authors propose Algebraic operational laws using algebraic norm for PyPHFNs. Furthermore, a list of aggregation operators, namely Pythagorean probabilistic hesitant fuzzy weighted average (PyPHFWA) operator, Pythagorean probabilistic hesitant fuzzy weighted geometric (PyPHFWG) operator, Pythagorean probabilistic hesitant fuzzy ordered weighted average (PyPHFOWA) operator, Pythagorean probabilistic hesitant fuzzy ordered weighted geometric (PyPHFOWG) operator, Pythagorean probabilistic hesitant fuzzy hybrid weighted average (PyPHFHWA) operator and Pythagorean probabilistic hesitant fuzzy hybrid weighted geometric (PyPHFHWG) operator, are proposed based on the defined algebraic operational laws. Also, interesting properties of these aggregation operators are discussed in detail.

PyPHFN is not only a generalization of the traditional IHFN, but also a more effective tool to deal with uncertain multi-attribute decision-making problems.

In addition, the authors design the algorithm to handle the uncertainty in emergency decision-making issues. At last, a numerical case study of coronavirus disease 2019 (COVID-19) as an emergency decision-making is introduced to show the implementation and validity of the established technique. Besides, the comparison of the existing and the proposed technique is established to show the effectiveness and validity of the established technique.

Paper is original and not submitted elsewhere.

The purpose of this study is to investigate the influence of capital adequacy ratio (CAR) prescribed in Basel III on the risk-taking behaviour of Islamic and conventional commercial banks in Malaysia. It also investigates the claim that the risk-taking behaviour of Islamic banks (IBs) and conventional banks (CBs) managers is identically influenced by CAR.

Secondary data for all CBs operating in the Malaysian banking sector are gathered from FitchConnect database for the 2011–2017 period. Both dynamic ordinary least squares and generalised method of moments techniques are used to estimate a panel data of 43 commercial banks, namely, 17 IBs and 26 CBs.

The findings of this study lend support to the favourable influence of CAR set in Basel III accord on risk-taking behaviour of both types of banks. CBs appeared to be remarkably better off in terms of capital buffers. Evidence is established on the identicality of the risk-taking behaviour of IBs and CBs managers under CAR influence.

Even though a high CAR is observed to hamper risk-taking of banks, the findings may serve as a signal to regulators to be mindful of the implications of holding a high CAR. Similarly, managers may capitalise on the findings in terms of strategising for efficient use of the considerable capital buffers. Shareholders are also concerned about managers’ use of the considerable capital buffers.

This study is among a few studies that endeavoured to provide empirical evidence on the claim that IBs mimic the conduct of CBs in light of the influence of CAR prescribed in Basel III on risk-taking behaviour, particularly banks operating within the same banking environment.

The aim of this research is to establish a new type of aggregation operator based on Hamacher operational law of spherical uncertain linguistic numbers (SULNs).

First, the authors define spherical uncertain linguistic sets and develop some operational laws of SULNs. Furthermore, the authors extended these operational laws to the aggregation operator and developed spherical uncertain linguistic Hamacher averaging and geometric aggregation operators.

The authors were limited in achieving a consistent opinion on the fusion in group decision-making problem with the SULN information.

In order to give an application of the introduced operators, the authors first constrict a system of multi-attribute decision-making algorithm.

The proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer, multi-item and a consolidated vendor store. Regarding demand and order quantities with the deterministic and type-1 fuzzy numbers, we have also formulated the classic/crisp MOVMI model and type-1 fuzzy MOVMI (T1FMOVMI) model. The suggested solution technique can solve both crisp MOVMI and T1FMOVMI problems. By finding the optimal ordered quantities and backorder levels, the Pareto-fronts are constructed to form the solution sets for the three models.

A multi-objective vendor managed inventory (MOVMI) is the most recognized marketing and delivery technique for the service provider and the retail in the supply chain in Industry 4.0. Due to the evolving market conditions, the characteristics of the individual product, the delivery period and the manufacturing costs, the demand rate and order quantity of the MOVMI device are highly unpredictable. In such a scenario, a MOVMI system with a deterministic demand rate and order quantity cannot be designed to estimate the highly unforeseen cost of the problem. This paper introduces a novel interval type-2 fuzzy multi-objective vendor managed inventory (IT2FMOVMI) system, which uses interval type-2 fuzzy numbers (IT2FNs) to represent demand rate and order quantities. As the model is an NP-hard, the well-known meta-heuristic algorithm named NSGA-II (Non-dominated sorted genetic algorithm-II) with EKM (Enhanced Karnink-Mendel) algorithm based solution method has been established.

The experimental simulations for the five test problems that demonstrated distinct conditions are considered from the real-datasets of SAPCO company. Experimental study concludes that T1FMOVMI and crisp MOVMI schemes are outclassed by IT2FMOVMI model, offering more accurate Pareto-Fronts and efficiency measurement values.

Using fuzzy sets theory, a significant amount of work has been already done in past decades from various points of views to model the MOVMI. However, this is the very first attempt to introduce type-2 fuzzy modelling for the problem to address the realistic implementation of the imprecise parameters.

Modern businesses strategically focus on improving the online purchase experience (OPE) of customers to acquire a long-term competitive edge. However, the intellectual knowledge structure of OPE research remains uncharted, necessitating further investigation. This study aims to provide a concise synthesis of the evolution, trends and advancements of consumers’ OPE research using bibliometrics.

Firstly, the authors inventorised the relevant OPE literature, and then the bibliometric trends and the domain’s performance (top articles, outlets and authors) were analysed and illustrated through tables and narratives. Secondly, science mapping tools (such as co-occurrence) and visualisation strategy were deployed to pinpoint relevant OPE research themes and highlight the domain’s intellectual structure.

The most significant findings concern the most prolific authors, outlets, most cited articles and five thematic clusters forming the ground for potential future research paths. Also, these thematic clusters depicted the intellectual knowledge structure that emerged from the OPE research domain.

This review may be helpful for future academic researchers to identify future research paths in the domain and practitioners to help make policy decisions while formulating and articulating their marketing strategy.

Deploying the VOSviewer and Bibliometrix-R software together, this review is most likely the first attempt to the best of the authors’ knowledge to provide a thorough bibliometric synthesis of the OPE research domain.

This study aims to provide the current and future state of United Nations’ Sustainable Development Goals (SDGs) in the higher education institutions (HEIs). Since the SDGs’ proliferation, HEIs have played a crucial part in meeting the goals. Despite the central role of HEIs in accomplishing the SDGs, there has been little attention in providing a comprehensive overview of the SDGs in relation to HEIs.

A total of 280 publications in the Web of Science database were analyzed through a bibliometric approach consisting of citation analysis, co-citation analysis and co-occurrence of keywords analysis. This review explores the current state of SDGs, its central themes of research streams and predicts future direction in the context of HEIs.

The findings would assist stakeholders to strategize the SDGs on HEIs, including the government and policymakers, university top management, benefactors and academics. Three main research streams were observed sustainable curriculum; challenges and barriers of SDGs; and COVID-19 and health management.

Implications suggest that to achieve the stipulated goals in the SDGs, proper planning and strategy should be aligned proportionate to the national agenda.

This paper presents a novel knowledge structure by mapping the most relevant SDGs in the context of HEIs based on bibliometric analysis.

This study aims to assess tribal women’s health information literacy in their daily lives. The specific objectives are to determine the tribe’s interest and frequency of seeking health-related information, to know their preferred health information sources and health-care methods for treatment and to find out the prospective barriers to searching for and finding health-related information.

A well-structured questionnaire was designed and surveyed among the tribal women of Khagrachhari, Bandarban and Mymensingh districts in Bangladesh. Stratified sampling was used, and 326 responses were retrieved. The collected data were analyzed using Statistical Package for Social Sciences version 20 and Microsoft Excel.

Most of the tribal women are satisfied with their current health condition. Though they are highly interested in health-related information, they are very unusual in terms of searching for this kind of information. Vaccination information is their most desired information, and allopathic treatment is highly preferred by them. In this regard, they consult with doctors at nearby community clinics or government hospitals for different health issues. However, health information terminologies are often difficult for them to understand. High costs, lack of awareness and distance from health centers are significant barriers for tribal women seeking health-related information.

To the best of the authors’ knowledge, this is the first known effort in a developing country to study tribal women’s concerns regarding health-related issues.

This research examines the bidirectional relationship between Environmental, Social and Governance (ESG) voluntary disclosure engagement and financial performance of a panel of banks extracted from the Gulf Cooperation Council (GCC) banking industry, covering a period of 11 years (2007–2017). We find that GCC banks, and in particular Islamic banks, voluntarily disclose low level of information related to ESG activities. Using system GMM methodology, we provide evidence that ESG disclosure adversely affects bank performance, regardless of the bank performance measure used. Thus spending on ESG turns out to be costly for GCC banks, a result that is consistent with the agency problem, where managers are likely to reduce long-term expenditures related to ESG actions in order to boost short-term profits. As managers' compensations often relate to short-term financial performance, managers tend to reduce their spending on ESG activities. Furthermore, contrary to previous research, our results indicate that the relationship between ESG and financial performance is bidirectional and dynamic. We also find evidence that ESG disclosure positively affects performance only for well-diversified banks. Finally, although conventional banks disclose significantly more information related to ESG activities, we do not find any significant differences between the two types of banks in the relationship between ESG disclosure and performance. Our suggestion is that these results are consistent with what we call “clientele” and “gravitation” effects, where a customer tends to choose to deal with the bank that reflects his religious beliefs (gravitation effect) and with the bank that provides him with the best services (clientele effect) regardless of its ESG disclosure.