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The COVID-19 outbreak has disrupted the habits of customers as well as their shopping behavior. This study aims to critically examine the associated benefits and challenges of online shopping from the perspective of customers in the COVID-19 pandemic.

A systematic review of the relevant literature published between 2020 and 2022 was conducted via performing comprehensive search query in leading scholarly databases “Scopus and Web of Science” with the restriction of their predefined subject category of “Business.” Overall, 30 research studies were selected for the review and a significant number of studies were published in 2021 (n = 15).

The research findings revealed that customers are motivated to shop online because of perceived benefits such as time-saving, convenience, 24/7 accessibility, interactive services without physical boundaries, trust, website attractiveness and cost-saving. However, challenging factors such as financial scams, privacy concerns, poor quality of products and services, fake promotions and reduced social interaction have hindered the growth of online shopping. The recommendations regarding designing marketing strategies, secured transaction, multiple payment options, trust building, protection of privacy, promotion via social media, effective mechanism to secure and timely delivery of product are helpful to improve the service quality of online shopping.

The outcomes of this research are valuable to online retailers and policymakers, as it highlights how the benefits can enhance customers’ shopping intentions and minimize the impact of associated challenges. This study also recommends the redesigning of user-friendly interfaces of online shopping websites and ensures their privacy, security and performance on a regular basis.

Amazon Explore is a new online experience product from Amazon, which offers live stream sightseeing of destinations around the world. This paper aims to provide a first insight into how exactly Amazon Explore enters the virtual experience (VE) industry, and discuss the possible implications of its business model for the future of virtual and offline travel experiences.

Qualitative and quantitative methods of content analysis methods were employed in this study. The sample of this research consisted of 175 Amazon Explore products. Firstly, the authors analysed the content of each product, and then quantitative method were used to present the data. With this analysis, the authors presented how Amazon Explore is testing the foundations for new business models, and discuss the possible implications for the future of tourism. One year later, those same Amazon Explore products were reviewed again to check development progress. The following were the main questions regarding VE: How interactive are Amazon Explore products? How does Amazon Explore aim to ensure the monetisation of these products in an economically sustainable way in order to go beyond the “freemium” business model, often associated with VE as just another destination marketing tool?

This article presents the discussions of VE and virtual reality (VR). The authors determined the level of interactivity of the diverse VE offered themes with a model of four levels of interactivity. The results show that the analysed products achieve mostly only low levels of interaction. Regarding monetisation, Amazon Explore shows three possible future directions in the development of VE: as a marketing tool, as an extension of the offline experience and as potentially someday replacing real travel as part of the future monetisation scenario.

The article offers the first insights into Amazon's extension into the realm of VE in two time periods in 2020 and 2021, and, based on these preliminary results, discusses four possible scenarios for the future development of VE monetisation.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

The purpose of the paper is to identify existing and common critical success factors adapted for implementing Industry 4.0 technology, which is essential to survive in the vulnerability, uncertainty, complexity and ambiguity (VUCA) environment by using systematic literature review (SLR) methodology with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) and content analysis strategy.

The SLR methodology with the PRISMA and content analysis strategy adapted to review 74 papers in peer-reviewed academic journals and industry reports published from 2014 to 2021.

Based on a review of relevant literature, two theoretical contributions have been added to the literature on Industry 4.0. First, this review reveals that 35 (47%) out of total 74 studies assessing the Industry 4.0 implementation in the manufacturing industry, the service industry can also create value through Industry 4.0 implementation, with a lot of potential to increase productivity, which literature has not explicitly focused on. Second, this paper proposes the 12 most common critical factors (training and development, organizational culture, top management support, organizational structure, innovation capability, technological infrastructure, security system, standardization of procedures, financial resources, communication and cooperation, change management and governance) that can be considered as the significant critical factors for successful implementation of Industry 4.0.

The novelty part related to methodological perspective by using the PRISMA approach for systematic review, which cannot be found extensively in existing literature in the context of the Industry 4.0 phenomenon to analyze critical factors.

This study explores the mediating effects of relationship marketing orientation (RMO) and service quality orientation (SQO) on market orientation, selling orientation, and policyholder retention in non-life insurance services. Additionally, it offers important recommendations for non-life insurers in Taiwan for policy development and improving policyholder retention.

Data were collected from a sample of policyholders belonging to the top five non-life insurance companies in Taiwan. The data were then analyzed with structural equation modeling.

RMO and SQO mediate the effects of the salesperson’s market orientation on policyholder retention. Thus, RMO and SQO are key factors influencing policyholder retention. Consequently, high levels of market orientation should be maintained to increase RMO and SQO, strengthening the retention rate of non-life insurance policyholders.

The main limitation of this study is its cross-sectional nature. In the future, researchers should collect data from other countries and service industries (e.g. banks, securities, and other financial institutions), expand to different insurance contexts (e.g. life insurance), and conduct longitudinal studies or experimental research.

The results of this study can act as a guide for providers of non-life insurance services. Based on the research results, we recommend decision-makers pay increased attention to increasing policyholder retention rates by strengthening their firm’s RMO and SQO.

Few studies have investigated the relationships among market orientation, selling orientation, RMO, SQO, and policyholder retention in non-life insurance services within Asian contexts in general and specifically in Taiwan. Thus, this study’s theoretical contributions, managerial implications (especially for decision-makers), and the proposed future research directions represent timely and valuable additions to the literature.

Due to the current volatile environment and fierce competition, manufacturing firms (MFs) must improve their performance to survive. In this regard, checking and monitoring the suppliers' risk should significantly improve the performance of MFs. In addition, a relation based on not being an opportunist, confidence and reliance are influential factors in reducing the supplier defaults on his/her supply obligations and improving supply chain performance (SCP). Besides, the moderator function of supplier involvement (SI) in the relationship between quality of the relationship (QoR) and supply risk mitigation (SRM) is undeniable.

Based on the survey of 148 samples from small to large-sized MFs in Jordan, Turkey and Egypt, empirical evidence has been conducted to support a majority of the authors’ hypotheses. This paper provides a theoretical review of buyer–supplier relationships and supply risk. Hypotheses were tested by using structural equation modeling (SEM)/Smart PLS-4.

According to the results, confidence and reliance have statistically significant and positive impacts on SRM, resulting in better SCP. Moreover, the findings show that SI positively affects and moderates the relationship between confidence (C) and SRM, while it has no statistically significant influence on the relationship between reliance (R) and SRM.

This study provides necessary material for managers and decision-makers in MFs to confirm the importance and understanding of the QoR in building relationships and business dealings with partners in the SC, in addition to limiting and mitigating the risks of an interruption in supply in particular. Therefore, building a high-quality relationship as a practice based on trust and reliability with suppliers positively affects the performance of the SCs of MFs.

This research paper offers empirical evidence for using QoR within SRM resources of MFs' context for enhancing their supply chain performance. This study is one of few studies that examine the QoR and SRM that contribute to enhancing SCP in MFs in developing countries, which also can serve as a reference for many SC managers and practitioners.

This study aims to investigate the moderating impact of environmental knowledge on the factors influencing individuals’ continuous intention to use e-wallets.

Using a quantitative research design, this study develops and empirically tests a structural model. A purposive sample of 344 e-wallet users in Jordan was analyzed using Smart-PLS software.

The results indicate that perceived usefulness, subjective norms and perceived behavioral control directly influence the intention to continue using e-wallets. Notably, environmental concern and environmental knowledge do not have a direct impact on continuous intention. However, they act as mediators in the relationship between perceived behavioral control and continuous intention. Specifically, environmental knowledge acts as a mediator between perceived behavioral control, subjective norms and continuous intention. Furthermore, environmental knowledge moderates the relationship between perceived behavioral control and subjective norms, significantly impacting users’ continuous intention to use e-wallets.

This study contributes to the extended theory of planned behavior model within the banking sector by emphasizing the enhanced explanatory power of environmental factors. It underscores the pivotal role of environmental knowledge as a moderator that connects determinants of e-wallet usage to continuous intention.

This paper aims to establish the causal relationship between destination image and tourist motivation and engagement.

A causal model with seven hypotheses was tested into a sample of 438 domestic tourists in Acapulco (Mexico).

Cognitive destination image is the main antecedent of tourist engagement, exerting an important direct and indirect effect through push and pull motivations. Affective image also exerts a direct effect on tourist engagement and an indirect effect through push and pull motivations. Only pull motivations exert an influence on tourist engagement.

The study is based on domestic tourists at a sun and beach destination.

Destination management organisations should invest in the care, improvement and promotion of tourism resources. Online and offline communication campaigns should be based on tourism resources and experiences.

This paper fulfils three research gaps: destination image is associated with tourist engagement; tourist motivations affect tourist engagement; and destination image is associated with tourist motivations.

This paper examines the factors which impact the behavioral intentions toward cryptocurrency based on signaling theory.

Data were collected through online questionnaire, and responses from 223 individuals in Lebanon were analyzed through SEM technique using Amos 24.

The outcomes portrayed the positive effect of perceived benefits and trust in cryptocurrency on behavioral intentions toward cryptocurrency; while not supporting the hypothesized influence of herd behavior and regulatory support.

This paper is among the first studies to adopt Signaling Theory (ST) in the cryptocurrency behavioral intentions research. Moreover, it is of the initial efforts in Lebanon and Middle East in evaluating behavioral intentions to use cryptocurrency, and it provide insights for future researchers, crypto project owners, crypto investors and crypto trading platforms.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.