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Since crude oil is crucial to the nation's economic growth, crude oil futures are closely related to many other markets. Accurate forecasting can offer investors trustworthy guidance. Numerous studies have begun to consider creating new metrics from social networks to improve forecasting models in light of their rapid development. To improve the forecasting of crude oil futures, the authors suggest an integrated model that combines investor sentiment and attention.

This study first creates investor attention variables using Baidu search indices and investor sentiment variables for medium sulfur crude oil (SC) futures by collecting comments from financial forums. The authors feed the price series into the NeuralProphet model to generate a new feature set using the output subsequences and predicted values. Next, the authors use the CatBoost model to extract additional features from the new feature set and perform multi-step predictions. Finally, the authors explain the model using Shapley additive explanations (SHAP) values and examine the direction and magnitude of each variable's influence.

The authors conduct forecasting experiments for SC futures one, two and three days in advance to evaluate the effectiveness of the proposed model. The empirical results show that the model is a reliable and effective tool for predicting, and including investor sentiment and attention variables in the model enhances its predictive power.

The data analyzed in this paper span from 2018 through 2022, and the forecast objectives only apply to futures prices for those years. If the authors alter the sample data, the experimental process must be repeated, and the outcomes will differ. Additionally, because crude oil has financial characteristics, its price is influenced by various external circumstances, including global epidemics and adjustments in political and economic policies. Future studies could consider these factors in models to forecast crude oil futures price volatility.

In conclusion, the proposed integrated model provides effective multistep forecasts for SC futures, and the findings will offer crucial practical guidance for policymakers and investors. This study also considers other relevant markets, such as stocks and exchange rates, to increase the forecast precision of the model. Furthermore, the model proposed in this paper, which combines investor factors, confirms the predictive ability of investor sentiment. Regulators can utilize these findings to improve their ability to predict market risks based on changes in investor sentiment. Future research can improve predictive effectiveness by considering the inclusion of macro events and further model optimization. Additionally, this model can be adapted to forecast other financial markets, such as stock markets and other futures products.

The authors propose a novel integrated model that considers investor factors to enhance the accuracy of crude oil futures forecasting. This method can also be applied to other financial markets to improve their forecasting efficiency.

There has been a lot of research on how to set marketing budgets, but the overlooked aspect was how allocating funds influences business performance in a multi-goal context. This study aims to examine the relationship between business performance, the process of allocating funds to multiple goals and the interaction among the goals.

Ratio data were generated through “a constant sum scale” from a sample of 362 managers from the B2C sector, besides data on after-tax revenue for two years. The data file was created. Then, a factor analysis was performed on the data. Furthermore, an econometric model with interaction terms was fitted to the data.

The results show that allocating funds to multiple marketing goals – demand generation, customer experience, brand image, marketing competency and purchase intention – influences business performance. Furthermore, a goal’s impact on business performance is higher when coupled with other goals than in isolation.

The findings of the study should assist managers in increasing revenue while spending less on marketing and shifting funds from less efficient goals and pairs of goals to highly efficient ones.

By extending the relevant theory on the relationship between the process of marketing fund allocation, multiple goals and business performance, this study contributes to the literature on marketing.

Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations.

The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF.

From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance.

Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly.

This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/

Despite the vast potential of mobile phone use, grape smallholder farmers’ satisfaction with mobile phone use has attracted insufficient attention among scholars in Tanzania. The study examined factors influencing satisfaction with mobile phone use for accessing agricultural marketing information.

The study used a cross-sectional research design and a mixed research method. Structured questionnaire and focus group discussions were used to collect primary data from 400 sampled grape smallholder farmers. Data were analysed inferentially involving two-way analysis of variance, ordinal logistic regression and thematic analysis.

The findings indicate a statistically significant disparity in grape smallholder farmers’ satisfaction across different types of agricultural marketing information. Grape smallholder farmers exhibited higher satisfaction levels concerning information on selling time compared to all other types of agricultural marketing information (price, buyers, quality and quantity). Factors influencing grape smallholder farmers’ satisfaction with mobile phone use were related to perceived usefulness, ease of use, experience and cost.

This study contributes to scientific knowledge by providing actionable insights for formulating unique strategies for smallholder farmers’ satisfaction with agricultural marketing information.

The purpose of this study is twofold. The first objective is to identify the factors that affect Gen Z tourists' M-payment behaviour. Next, this study investigates the inter-relationship between Gen Z tourist’s perception of M-payment benefits, adoption behaviour, usage risk and future usage intention.

The sample comprised Malaysian Gen Z individuals (n = 326) who had experience using M-payment methods while travelling outbound. Given the complex nature of the model and the goal to predict and explain relationships within Gen Z's M-payment usage, partial-least square-structural equation modelling was used to assess the study framework and test the proposed relationships.

This study reveals significant influences on Gen Z tourists' behavioural intentions towards M-payment usage. Perceived benefits, performance expectancy, social influence and perceived trust positively impact behavioural intentions, while effort expectancy exhibits no significant effect. Furthermore, perceived trust is strongly influenced by perceived security, which also positively influences behavioural intentions. A mediated relationship is evident as trust mediating the effect of perceived security on behavioural intentions.

This study’s findings contribute to understanding the intricate relationships influencing Gen Z's M-payment behaviour and underscore trust's pivotal role in mediating the security–behavioural intention relationship.

This study is among the first to consider Mental Accounting Theory and the Unified Theory of Acceptance and Use of Technology as crucial underpinning theories in comprehending the intricate relationships that influence Gen Z travellers' perceptions and behaviours concerning M-payment systems.

This study aims to examine the impact of the gameful experience on behavioural outcomes. Drawing from stimulus–organism–response theory, it proposes and tests a new model that investigates the relationship between the gameful experience, brand loyalty and intention to use gamified branded applications in the sports context. In addition, it explores the mediating role of customer–brand engagement (CBE) and the moderating role of self-image congruity (SIC).

A sample of 436 active users of sport-related branded gamified applications was used to test the model. Data was collected from online sports forums, brands’ Facebook communities and during sporting events.

Results indicate that the gameful experience positively and directly impacts behavioural intentions but does not directly influence brand loyalty. This relationship becomes partially significant when mediated by CBE. In addition, results show that users with high levels of SIC are more likely to continue using the gamified application, whereas users with low levels are more likely to engage with the brand.

This study expands the gamification literature in the sports sector by revealing the importance of the gameful experience in driving loyalty, behavioural intentions and CBE. It proposes a new model that sheds light on the emotional aspect of the interaction between a user and a gamified system and the importance of exploring the effects of moderators, such as SIC, in these relationships.

Drawing on symbolic interaction theory (SIT), this study aims to identify what makes corporate social responsibility (CSR) communication more favorable to customers in the chain restaurants context. Specifically, this study examines the direct relationships between the interactivity of CSR communication, brand trust and brand sincerity. In addition, the mediating role of brand trust (i.e. separate dimensions of brand reliability and intentions) and the moderated mediating role of self-congruity are explored.

A total of 418 US consumers with past experiences of participating in CSR campaigns organized by chain restaurants on social media were recruited using the online survey method of nonprobability sampling through Amazon Mechanical Turk in December 2021.

The results of this study revealed that the interactivity of CSR communication on social media affects brand sincerity; brand reliability and brand intentions mediate the positive effect of interactivity of CSR communication on brand sincerity; and customer’s self-congruity moderated the positive mediation effect via brand reliability.

Chain restaurant marketers need to understand the important role of interactivity as a key element of CSR communication on social media to help develop brand trust and brand sincerity in chain restaurants.

This study expands on SIT to support the symbolic benefits of interactive CSR communication on social media.

Anthropomorphized brands have been widely used as marketing communication tools to engage consumers on social media, especially on Twitter. Guided by the social exchange theory (SET) and the dialogic theory, this study aims to investigate how anthropomorphized brands leverage different communication strategies on Twitter and how these strategies are related to consumer engagement.

Supervised machine learning was used to identify the communication strategies (i.e. message types and dialogic principles) of 125,887 tweets from 21 brand characters. Some statistical analyses (e.g. frequency analysis, Chi-square analysis and Poisson regression analysis) were performed to explore the relationships between communication strategies and consumer engagement (i.e. retweets and replies).

The majority of anthropomorphized brands’ tweets belonged to the socioemotional category and the most adopted dialogic principles were generation of return visits and conservation of visitors. Consumers engaged more with socioemotional tweets as well as the tweets that adopted the principles of dialogic loop and conservation of visitors. There were clear relationships between message types and dialogic principles in anthropomorphized brands’ tweets, and certain dialogic principles were found to effectively improve consumer engagement with certain message types.

To the best of the authors’ knowledge, this study is the first to investigate the communication strategies of anthropomorphized brand characters on Twitter using computational research methods. It not only provides brand managers a systematic review of how current anthropomorphized brands communicate with consumers on Twitter and what strategies work more effectively to trigger consumer engagement but also contributes to theory building in brand management by integrating the SET and the dialogic theory in brand anthropomorphism research.

This study aims to elucidate the role of curved walls in the presence of identical mass of porous bed with identical heating at a wall for two heating objectives: enhancement of heat transfer to fluid saturated porous beds and reduction of entropy production for thermal and flow irreversibilities.

Two heating configurations have been proposed: Case 1: isothermal heating at bottom straight wall with cold side curved walls and Case 2: isothermal heating at left straight wall with cold horizontal curved walls. Galerkin finite element method is used to obtain the streamfunctions and heatfunctions associated with local entropy generation terms.

The flow and thermal maps show significant variation from Case 1 to Case 2 arrangements. Case 1 configuration may be the optimal strategy as it offers larger heat transfer rates at larger values of Darcy number, Da_m. However, Case 2 may be the optimal strategy as it provides moderate heat transfer rates involving savings on entropy production at larger values of Da_m. On the other hand, at lower values of Da_m (Da_m ≤ 10⁻³), Case 1 or 2 exhibits almost similar heat transfer rates, while Case 1 is preferred for savings of entropy production.

The concave wall is found to be effective to enhance heat transfer rates to promote convection, while convex wall exhibits reduction of entropy production rate. Comparison between Case 1 and Case 2 heating strategies enlightens efficient heating strategies involving concave or convex walls for various values of Da_m.

A front-of-package label is a simple and effective way to communicate nutrition information to consumers. However, the use of the label has been limited to product packages. The purpose of this study is to explore the applicability of a front-of-package label to food print advertisements and to examine how the degree of nutrient content on the label influences consumer perceptions and behavioral intention.

Many food product manufacturers voluntarily use a front-of-package nutrition label showing specific information per serving size for calories, saturated fat, sodium and sugar. This exploratory, experimental research evaluates the thoughts, feelings and behavioral intention changes of consumers in response to a front-of-package label on a print advertisement and a product package. Two experiments were conducted online.

The presence of a front-of-package label in the ad increases ad responses involving perceived healthfulness of the product, ad attitude, brand attitude, healthy brand image and purchase intention. In addition, the healthier nutrient content listed on the label positively affects the audience’s responses. However, the front-of-package label on the product package increases only perceived healthfulness. Information about the degree of nutrient content indirectly influences intention to purchase the advertised healthy/unhealthy product sequentially via perceived healthfulness of the product, ad attitude, brand attitude and healthy brand image.

To generalize the results, various product categories should be tested with the same research design in future studies.

This study recommends that communication practitioners place a front-of-package label on their print advertisements even though the food is not healthy. However, practitioners should keep in mind that a front-of-package label does not increase sales in the long term if the product is unhealthy.

The major contribution of this study is its exploration of the applicability of a front-of-package label to the advertising context. The label plays a role as a message cue a consumer can use to evaluate the ad, brand and product.