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The Internet of Things (IoT) cloud platforms provide end-to-end solutions that integrate various capabilities such as application development, device and connectivity management, data storage, data analysis and data visualization. The high use of these platforms results in their huge availability provided by different capabilities. Therefore, choosing the optimal IoT cloud platform to develop IoT applications successfully has become crucial. The key purpose of the present study is to implement a hybrid multi-attribute decision-making approach (MADM) to evaluate and select IoT cloud platforms.

The optimal selection of the IoT cloud platforms seems to be dependent on multiple attributes. Hence, the optimal selection of IoT cloud platforms problem is modeled as a MADM problem, and a hybrid approach named neutrosophic fuzzy set-Euclidean taxicab distance-based approach (NFS-ETDBA) is implemented to solve the same. NFS-ETDBA works on the calculation of assessment score for each alternative, i.e. IoT cloud platforms, by combining two different measures: Euclidean and taxicab distance.

A case study to illustrate the working of the proposed NFS-ETDBA for optimal selection of IoT cloud platforms is given. The results obtained on the basis of calculated assessment scores depict that “Azure IoT suite” is the most preferable IoT cloud platform, whereas “Salesman IoT cloud” is the least preferable.

The proposed NFS-ETDBA methodology for the IoT cloud platform selection is implemented for the first time in this field. ETDBA is highly capable of handling the large number of alternatives and the selection attributes involved in any decision-making process. Further, the use of fuzzy set theory (FST) makes it very easy to handle the impreciseness that may occur during the data collection through a questionnaire from a group of experts.

This study aims to evaluate the relationship between the estimated levels of diet advanced glycation end products (dAGEs) intake and obesity in university students.

This cross-sectional study included 301 university students aged 18–30 years. dAGEs was estimated using a food frequency questionnaire, for 549 routinely consumed food items and were reported by dividing total energy intake. Dietary intake and sociodemographic data were collected using validated questionnaires, and the anthropometric characteristics were measured. The relationship between anthropometric measurements and dAGEs intake was examined by binary logistic regression.

A total of 43.2% of the participants had high levels of dAGEs. A significant decreasing trend was found in the percentage of carbohydrate intake compared to the increasing trend in dAGEs consumption (p = 0.005). The percentage of fat intake and meat consumption were significantly higher in participants with the highest consumption, compared with the lowest consumption of dAGEs (p = 0.006). According to the dAGEs classification of participants, body mass index, waist circumference and energy intake were found to be significantly related in all model groups. Accordingly, the increase in body mass index, waist circumference and energy intake were determined as a risk factor in those with high dAGEs intakes.

The findings of this study emphasized that higher intake of dAGEs was associated with an increased risk of obesity parameters in college students.

Breakthrough technological innovation is of vital significance for firms to acquire and maintain sustainable competitive advantages. The construction of an innovation ecosystem and the interaction with heterogeneous participants have emerged as a new dominant model for driving sustained breakthrough technological innovation in firms. This study aims to explore the effects of collaborative modes within the innovation ecosystem on firms’ breakthrough technological innovation and the ecological legitimacy mechanisms involved.

The research employs data from 212 innovative firms and conducts empirical research using a two-stage structural equation modeling (SEM) and artificial neural network (ANN) analysis.

The results indicate that firm-firm collaboration (FF), firm-user collaboration (FU), firm-government collaboration (FG), firm-university-institute collaboration (FUI) and firm-intermediary collaboration (FI) all have significant positive effects on breakthrough technological innovation (BTI), with FU being particularly crucial. Furthermore, the results confirm the positive moderating effects of ecological legitimacy (EL) on the relationships between FF and BTI, as well as between FU and BTI. Conversely, EL has a negative moderating effect on the relationship between FUI and BTI, as well as between FI and breakthrough technological innovation. Additionally, EL does not have a significant influence on the relationship between FG and BTI.

Through resource dependence theory (RDT), this study unveils the black box of how collaboration modes within innovation ecosystems impact breakthrough technological innovation. By introducing ecological legitimacy as a contextual factor, a new research perspective is provided for collaboration innovation within innovation ecosystems. The study employs a combination of SEM and ANN for modeling, complementing nonlinear relationships and obtaining robust results in complex mechanisms.

This study delves into how corporations make decisions about influencer marketing. Specifically, it examines the differences between human influencers, who carry the risk of scandals, and virtual influencers, a new and unpredictable realm, regarding their integration with social media platforms.

Using game theory and empirical data, the study explores crucial factors in influencer marketing, including influencer quality, reputation repair costs and the probability of R&D failures.

This study suggests that companies favor human influencers when the risk of scandal is low. However, competing companies switch to virtual influencers at different intervals as this risk increases. The costs, likelihood of scandals and competition intensity all play a role in a company's decision-making regarding technology management. Additionally, a higher chance of R&D failure can motivate a company to invest more in R&D to gain a competitive advantage over rivals that may suffer failures.

This study provides insights into how corporations manage social media influencer marketing in the digital age. It contributes to marketing theory and technology management decisions by offering a fresh perspective on the relationship between corporate reputation and influencer marketing strategy.

This study offers valuable perspectives into a relatively uncharted area of marketing strategy. It employs game theory and empirical analysis to introduce a fresh method of comprehending the dynamics of influencer marketing, its impact on corporate reputation management and its interaction with social media.

This study aims to understand the impact of negative supervisor gossip on job performance among South Indian hotel employees. The focus is not just on the direct influence, but also on the mediating role of feedback-seeking behaviour (FSB) and the moderating effects of the agreeableness trait.

Through purposive sampling, data was garnered from South Indian hotel employees. Comprehensive analyses were performed using partial least squares structural equation modelling.

The analysis shows that FSB plays a mediating role in the positive relationship between negative supervisor gossip and job performance. In addition, the influence of gossip on FSB and subsequent job performance was more pronounced for employees with high agreeableness.

This research underscores the complex interplay between negative supervisor gossip and job performance, revealing that such gossip can catalyze FSB process in employees. It suggests that under certain conditions, negative gossip can be transformed into a constructive force that enhances job performance, challenging traditional perceptions of gossip in the workplace.

The findings underscore the importance of understanding the effects of workplace dynamics, like supervisor gossip, on employee behaviour and performance. Recognizing the influence of individual personality traits, such as agreeableness, can guide management strategies for fostering a productive work environment.

This research sheds light on the intricate interplay between negative supervisor gossip, FSB and agreeableness, offering a novel perspective on their combined impact on job performance. It not only enriches the existing literature on workplace communication but also broadens the understanding of the role of personality traits in shaping employee responses and outcomes.

Prior studies have found that managers adjust operational activities to tackle climate risk. However, the effects of climate risk on accounting practices are largely ignored in the literature. This paper investigates whether and how climate risk influences managers’ decision-making on the level of accounting conservatism and explains the results based on two competing channels: valuation demand and contracting demand.

Using firm level climate risk measures, we build a modified Basu (1997) model to conduct our econometric tests. In the baseline model, we use earnings before extraordinary items as the dependent variable, referred to as the earnings model. We control for different levels of fixed effect to identify the shocks of climate risk and mitigate potential concerns on endogeneity and bias in the model. A series of robustness tests provide supporting evidence for our baseline results and our explanation.

Using a sample of 35,832 firm-year observations on listed US firms over the period 2002 to 2019, we find that the perception of climate risk drives managers to choose the less conservative accounting policies. We conclude that the results are consistent with the valuation demand explanation but inconsistent with the contracting demand explanation.

The study provides additional evidence on how managers respond to climate risk by adjusting their corporate polices, specifically accounting policies. Our findings contradict the results of prior studies. We explain our results from a unique perspective. Overall, the study provides valuable insights for academics, investors, managers and policymakers.

Sustainable development is considered a key factor in addressing environmental issues, global inequalities and poverty. This study aims to investigate the impact of stock market indicators on sustainable development across 16 emerging markets from 2003 to 2020.

The research uses causality and cointegration analyses to explore the relationships between stock market indicators and sustainable development.

Univariate causality analysis reveals a bidirectional causal relationship between the stock market turnover ratio and sustainable development, as well as a unidirectional relationship from sustainable development to stock market capitalization and total value traded. Panel-level cointegration analysis suggests that only stock market capitalization has a weak positive influence on sustainable development. However, the impact of stock market indicators on sustainable development varies significantly among countries, as revealed by country-level cointegration analysis.

While this study provides valuable insights, it is not without limitations. The findings are limited to the selected emerging markets and the specified timeframe (2003–2020). The complexity of factors influencing sustainable development suggests the need for further exploration in diverse contexts.

Understanding the nuanced relationships between stock market indicators and sustainable development can offer valuable insights for policymakers, investors and stakeholders.

This research contributes to the existing literature by examining the multifaceted connections between stock market indicators and sustainable development, focusing on country-specific causality relationships. The study highlights the reciprocal nature of this relationship, where financial market development can both influence and be influenced by a country's progress toward sustainability. This approach provides a more nuanced understanding of the complex interaction between stock market maturity and sustainability goals.

Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.

This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.

The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.

Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

The study aims to advance the current state-of-the-art and identify the main theories, methodologies and research gaps. In this article, we examine the network perspective on resource interaction in management, systematically reviewing 92 published articles in peer-reviewed journals from 2013 to 2023.

This systematic literature review is a methodical, transparent and replicable approach to choosing and evaluating scientific works. We have analyzed and combined all the available evidence, giving a comprehensive overview of the current state of the literature.

The subject is still under development in the literature, so there are still some research gaps, such as lack of information about markets and competitiveness. The main thematic groups we found included the firm’s social media, business performance, innovation in organizations, social media and big data, network analysis and artificial intelligence.

It is important to note that the subject is still under development in the literature, so there are still some research gaps, such as some lack of information about markets and competitiveness, the online presence of luxury brands and the impact of technology on their performance, which is not approached in the literature; some companies find it challenging to adopt new technologies; what level of technology and academic specialization is needed to measure performance; how to measure the level of credibility of information shared on the internet and the psychological impact of artificial intelligence on future generations and communication.

Managers can use this study to improve network strategies for better communication with diverse stakeholders and adopting new technologies, especially to enhance skills among older generations. Networks play a crucial role in fostering social capital among firms, facilitating knowledge management and improving the quality of processes. The resilience of business networks serves as a mediator between responsible innovation and a company's performance. Managers may consider expanding the use of networks to other areas of management to promote organizational collaboration and professional networking. Employees can also act as brand ambassadors for their organizations, helping to establish informal networks and increase visibility.

An integrative framework and a future research agenda are presented, with the potential to advance our understanding in this field.

E-commerce expands product and service reach, emphasizing the need for strategic market approaches to enhance e-service quality and drive sales growth. This paper aims to assess the relationship between the perceived quality of e-commerce platforms (characterized by measures of order and return convenience), customer satisfaction with online shopping and repurchase intention from online stores as well as examine whether demographic variables such as age, gender and area of residency (urban/rural) influence the ratings of each of these variables.

An online, self-administered survey gathered 108 valid responses from e-commerce customers. Data were analyzed in Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) through principal component analysis, confirmatory factor analysis and structural equation modeling (SEM) as well as correlation, descriptive statistics, difference of means tests and nonlinear regression.

Online shopping on e-commerce platforms is seen as convenient for both placing orders and managing returns. Additionally, consumers express satisfaction with their online shopping experiences and exhibit a strong intention to repurchase. The analysis revealed linear relationships between order convenience and customer satisfaction, between order convenience and repurchase intention and nonlinear relationships between return convenience, customer satisfaction and repurchase intention. No significant difference was found between the way the demographic variables rated the convenience, satisfaction and repurchase intention constructs.

This study contributes to the empirical literature on service quality in e-commerce by providing a streamlined model of the interactions among the factors as well as by isolating the nonlinear relationships and comparing results across three demographic variables. From a managerial standpoint, the findings suggest that strategies aimed at providing complete qualitative information and enhancing order and return convenience improve customer satisfaction and foster repurchase intention.