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The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent findings regarding consumer engagement behavior. To address this knowledge deficit, we contribute to the consumer engagement literature by developing and testing a conceptual model that explores and explains the relationships between the factors that influence continued engagement intention (CEI), a form of behavioral intention.

A literature review was conducted to identify gaps and develop a theoretically informed conceptual model and hypotheses. Survey data from 604 Instagram SMI followers were analyzed using partial least squares structural equation modeling using SmartPLS 3.3.3 to assess the structural model relationships and conduct post hoc analysis.

The findings suggest that it is important to positively influence consumer responses to elicit CEI. Furthermore, homophily attitudes toward SMIs moderate the relationship between SMI experience and CEI.

Brands must work with SMIs to create positive SMI experiences and develop CEI. Furthermore, SMIs should focus on brands that fit their lifestyles to enhance homophily attitudes and forge CEI.

This study contributes to the literature by combining social exchange and flow theories to develop and test a holistic framework for examining CEIs regarding SMIs and brands. The findings show that creating positive SMI experiences benefits brands seeking CEI.

The study aims to explore the impact of ownership concentration (OC) on bank financial distress (FD). Furthermore, the bank’s financial stability levels determine the association between the two.

Bank data of 33 Indian commercial banks are procured for ten years (2013–2022). The panel data econometrics is applied for empirical estimations. The quantile regression approach is used to determine the association between OC and FD at different quantiles of the FD. Non-normalcy of the data is checked and ensured before applying the quantile regression.

Surprisingly, it is found that promoters have a nonlinear impact on the firm’s stability. The inverted U-shape result implies that as promoters cross a threshold level, the benefit of increasing promoters’ stake takes a beating and a further increase in promoters’ stakes adversely impacts the stability of the banks. Moreover, this threshold value increases while moving from low to high levels of stability in a quantile regression application.

This study uses promoters as the proxy for OC. Other existing definitions of OC are not used in the study, which can further improve the robustness of the results. Additionally, the use of the type of ownership (private, public or foreign) is also not adopted in the present study. Both the limitations can be the study’s future scope on the topic.

The high OC is supposed to influence corporate governance adversely. Therefore, policymakers recommend low OC for better governance. However, the present study finds evidence that a higher OC (high threshold of OC as the stability increases) would be better for financial stability. This situation demands a trade-off between governance and financial stability regarding OC.

The authors do not observe any study having the nonlinear impact of OC on financial stability (opposite of FD). Moreover, the threshold of OC for the optimum level of financial stability increases as stability goes high. This evidence using quantile regression and finding the turning point using a quadratic equation is also not seen in the literature.

This review investigates the effects of temporal aggregation and systematic sampling on time-series analysis, focusing on their influence on data accuracy, interpretability and statistical properties. The purpose of the study is to synthesise existing literature on the topic and offer insights into the trade-offs between these data reduction techniques.

The research methodology is based on an extensive review of theoretical and empirical studies covering univariate and multivariate time series models, focusing on unit roots, ARIMA, GARCH, cointegration properties and Granger Causality.

The key findings reveal that while temporal aggregation simplifies data by emphasising long-term trends, it can obscure short-term fluctuations, potentially leading to biases in analysis. Similarly, systematic sampling enhances computational efficiency but risks information loss, especially in non-stationary data, and may result in biased samples if sampling intervals coincide with data periodicity. The review highlights the complexities and trade-offs involved in applying these methods, particularly in fields like economic forecasting, climate modelling and financial analysis.

The originality and value of this study lie in its comprehensive synthesis of the impacts of these techniques across various time series properties. It underscores the importance of context-specific applications to preserve data integrity, offering recommendations for best practices in the use of temporal aggregation and systematic sampling in time-series analysis.

This paper aims to trial a novel method of improving the performance of rail systems. Accordingly, an evaluation of rail system dynamics (SD) using discrete event simulation (DES) will be undertaken. Globally, cities and their transportation systems face ongoing challenges with many of these resulting from complicated rail SD. To evaluate these challenges, this study utilized DES as the basis of the analysis of Melbourne Metro Rail's SD. The transportation SD processes including efficiency and reliability were also developed.

Using DES, this research examines and determines the Melbourne Metro Rail's SD. Although the Melbourne Metro Rail is still in progress, the DES developed in this research examined the system requirements of functionality, performance and integration. As the basis of this examination, the Melbourne Metro Rail's optimization was simulated using the developed DES. As the basis of the experiment, a total of 50 trials were simulated. This included 25 samples for each of efficiency and reliability. The simulation not only scrutinized the SD but also underlined some of its shortfalls.

This study found that information and communication technology (ICT) was the pinnacle of system application. The DES development highlighted that both efficiency and reliability rates are the essential SD and thus fundamental for Melbourne Metro Rail system functionality. Specifically, the three elements of SD, capacity, continuity and integration are considered critical in improving the system functionality of Melbourne Metro Rail.

This particular mega rail infrastructure system was carefully analyzed, and subsequently, the DES was developed. However, since the DES is at its inception, the results are relatively limited without inclusive system calibration or validation process. Nonetheless, with some modifications, such as using different KPIs to evaluate additional systems variables and setting appropriate parameters to test the system reliability measures at different intensities, the developed DES can be modified to examine and evaluate other rail systems. However, if a broader system analysis is required, the DES model subsequently needs to be modified to specific system parameters.

Through evaluation of Melbourne's Metro Rail in the manner described above, this research has shown the developed DES is a useful platform to understand and evaluate system efficiency and reliability. Such an evaluation is considered important when implementing new transport systems, particularly when they are being integrated into existing networks.

Efficient rail networks are critical for modern cities and such systems, while inherently complex, aid local economies and societal cohesion through predictable and reliable movement of people. Through improved system functionality and greater efficiencies, plus improved passenger safety, security and comfort, the traveling public will benefit from the enhanced reliability of the transportation network that results from research as that provided in this paper.

This research paper is the first of its kind specifically focusing on the application of DES on the Melbourne Metro Rail System. The developed model aligns with the efficiency optimization framework, which is central to rail systems. The model shows the relationship between increased efficiency and optimizing system reliability. In comparison with more advanced mathematical modeling, the DES presented in this research provides robust, but yet rapid and uncomplicated system enhancements. These findings can better prepare rail professionals to adequately plan and devise appropriate system measures.

This study provides an overview of the numerous theoretical facets of greenwashing (GW) and their relationship with sustainability, social responsibility and sustainable development. This study highlights the actions of governments and international organizations in GW. It delves into the sins of GW and the various metrics used in the literature to measure them. It seeks to distinguish between sustainability reporting and GW practices by offering a critical perspective on GW.

This study measures GW practices at the international level and compares them with the ESG disclosure score. The main determinants of GW are assessed by examining the impact of a set of variables on GW. The influence of various sources used to gather the data were assessed using multiple regression analysis.

Factors such as protocols and conventions, media role and the strength of environmental policies have a considerable and positive impact on the occurrence of GW.

Owing to the research method chosen for measuring variables such as GW scores, procedures for measuring GW in companies should be developed. Multicriteria modeling could be a suitable approach to address the sorting or portfolio approach.

This study provides a theoretical basis for examining GW from a business-economic standpoint. It presents various perspectives on GW, analyzes relevant theories and explores potential GW strategies. This study highlights the connection between GW and various factors, including the influence of conventions, role of the media and strength of environmental policies.

As artificial intelligence technology empowers service robots, they increasingly communicate with consumers in a human-like manner. This study aims to investigate the effect of service robots’ different conversational styles (competent conversational style vs. cute conversational style) on consumer service acceptance and demonstrate the moderating role of consumers’ technology anxiety.

Based on anthropomorphism theory and social presence theory, the authors conducted two scenario-based experiments (restaurant scenario and hotel scenario) to investigate this issue.

The results indicate that service robots’ conversational styles impact consumers’ willingness to accept the use of service robots through perceived social presence and positive emotion. Moreover, consumers perceived social presence and positive emotion play a serial mechanism. In addition, the effect of competent conversational style on consumers perceived social presence is less effective than that of cute conversational style. Finally, the authors demonstrate the moderating role of consumer technology anxiety in the relationship between conversational styles and perceived social presence.

To provide consumers with a positive human–robot interaction experience at the service front line, managers need to make better use of the conversational styles of service robots by comprehensively considering the characteristics of consumer technology anxiety.

This research extends the literature on service robots by integrating consumer characteristics and robots’ conversational styles. These findings highlight the effectiveness of cute conversational style in alleviating consumer technology anxiety.

Current research in the field of behavioural finance has attempted to discover behavioural biases and their characteristics in individual investors’ irrational decision-making. This study aims to find out how biases in information based on knowledge affect decisions about investments.

In step one, through existing research and consultation with specialists, 13 relevant items covering major aspects of bias were determined. In the second step, multiple linear regression and artificial neural network were used to analyse the data of 337 retail investors.

The investment choice was heavily impacted by regret aversion, followed by loss aversion, overconfidence and the Barnum effect. It was observed that the Barnum effect has a statistically significant negative link with investing choices. The research also found that investors’ fear of making mistakes and their tendency to be too sure of themselves were the most significant factors in their decisions about where to put their money.

This research contributes to the expansion of the knowledge base in behavioural finance theory by highlighting the significance of cognitive psychological traits in how leading investors end up making irrational decisions. Portfolio managers, financial institutions and investors in developing markets may all significantly benefit from the information offered.

This research is a one-of-a-kind study, as it analyses the emotional biases along with the cognitive biases of investor decision-making. Investor decisions generally consider the shadowy side of knowledge management.

This paper aims to investigate the impact of perceived usefulness of online reviews and crowd cues on restaurant selection. In addition, the authors also examine the moderating role of perceived crowding and gender in this process.

The proposed hypotheses were tested with survey data (N = 200) collected from customers visiting full-service restaurants in Malaysia. The data were analyzed using SEM through Smart PLS.

The findings supported that the perceived usefulness of online reviews and perceived crowding have a positive effect on a consumer's purchase intentions, i.e. their decision of restaurant selection. Besides, a higher level of perceived crowding strengthens the relationship between the perceived usefulness of online reviews and their purchase intentions. This finding delineates that consumers prefer to dine in a crowded place with useful online reviews in an unfamiliar place. Finally, the results show that the effect of the usefulness of online reviews on purchase intentions does not vary with respect to gender (no significant contingent effect). However, the effect of perceived crowding varies with respect to gender – male customers have higher intentions to join crowded restaurants as compared to females.

Limitation of this study is its cross-sectional research design; data were collected in a single time frame. Longitudinal research design can be used to get in-depth knowledge of this phenomenon. Secondly, a non-probability sampling technique was used in this study, future research can used probability sampling technique to enhance generalizability of the study. Moreover, this study focused on the human crowding aspect, future studies can cover both aspects of crowding (human crowding and spatial crowding) in retailing or other service sectors (Blut and Iyer, 2020).

This study has multiple practical implications.

This study extends the current research on usefulness of online reviews and perceived crowding by investigating its direct and conditional effects. Specifically, the authors contribute in extant research by explaining its differential effects for male and female customers, when they select which restaurants to dine.

This study aims to explore how service delivery can be enhanced through digital transformation in the public sector in South Africa.

This case study used a qualitative research approach to obtain data through semi-structured interviews. The units of analysis were made up of individual professionals limited to purposive sampling to select chief information officers, investigators and administrative officers from national government departments and state-owned enterprises. The collected data from 12 participants was thematically analysed. The findings revealed that the government lacks legislation and strategy for digital transformation, leading to inconsistent implementation of digital transformation that enhances service delivery in the public sector of South Africa.

The findings revealed that the government lacks legislation and strategy for digital transformation, leading to inconsistent implementation of digital transformation that enhances service delivery in the public sector of South Africa.

The study was limited to the public sector of South Africa; however, its recommendations are applicable to all organisations that need to provide their services using digital transformation.

Practically, the implications of this study will serve as a resourceful benchmark for the public sector and other organisations.

Socially, the implications of this study ensure proper implementation of its recommendations to enhance service delivery in the public sector and other organisations.

Regarding the value that this study brings, it proposes an amendment of the current legislative framework in favour of one that covers digital transformation, which has become dominant in today’s enhanced provision of service delivery.

This paper examines the moderating effects of online reviews on the relationship between country image, product image, and purchase intention of products from two developed countries in Vietnam.

This current research used a cross-sectional design. Data was collected via questionnaires, and 305 responses were left after refining. The collected data were analyzed using exploratory factor analysis, confirmatory factor analysis, structural equation modeling, and multi-group analysis methods.

Affective country images do not directly affect purchase intention when online review quality and positivity are high. Cognitive country images still directly affect purchase intention when online review positiveness is low. However, online review quantity does not moderate the effects of country images on product images and purchase intention.

Cognitive country image consistently affects purchase intention through the central route independent of online reviews. In contrast, the affective country image will likely affect purchase intention through the peripheral route when online reviews are insufficient for customers.

Firms can mitigate the adverse effects of country image, especially cognitive country image, in foreign markets by improving online review quality and positiveness.

Our study extended existing literature by providing a better understanding of the nature of country image and the roles of country image dimensions in shaping product image and purchase intention in the context of the increasing popularity of online reviews.