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This research empirically studies consumers' continued intention to use mobile food delivery applications (apps) during the post-pandemic era in Saudi Arabia.

Using the unified theory of adoption and use of technology 2 (UTAUT2) as a theoretical model, this study collected data from a survey of 304 Saudi Arabian consumers. Structural equation modelling (SEM) was used to examine the proposed model and its hypotheses.

Social influence and performance expectancy (PE) had the strongest effects on the intention to continue using mobile food delivery apps in the post-pandemic era. In addition, effort expectancy (EE) significantly influenced PE regarding the adoption of food delivery apps. Meanwhile, EE was not an important predictor of the continued intention to use mobile food delivery apps in Saudi Arabia.

This study enriches the literature on consumers' continued intention to use food delivery apps in the post-pandemic era, a subject that has rarely been studied. In addition, this study expands the theoretical potential of the UTAUT2 model by examining the role of trust in continued intention and the effect of PE on EE in the adoption of food delivery apps during the post-pandemic era in Saudi Arabia.

The present study intends to discover and analyze the determinants of users' intention to use (ITU) drone-based online food delivery (OFD) services. The study mainly focuses on the drone-based food delivery system in India and its implications.

This study has used the purposive sampling method. With the support of the technology acceptance model (TAM) and the theory of planned behavior (TPB), a theoretical model was developed conceptually. Later, the model was validated using the partial least square-structure equation modeling (PLS-SEM) technique with consideration of 324 responses mainly from university students in Delhi- National Capital Region (NCR).

The findings reveal that all the determinants are positively and significantly related to ITU, except for perceived behavioral control that does not influence the consumer’s ITU drone-based OFD services. The study also shows that how food delivery system through drone can revolutionize the entire food delivery system in India.

The present study has developed a unique model that can be used by practitioners, future researchers in this field and policymakers in government departments. The present study is limited to Delhi-NCR in India, and thus, there is an issue of generalizability in the present study.

This study has examined the future of food delivery system through drone-based system. Thus, the leaders in the food industry will be better positioned to understand consumers' intentions to use OFD services using drones and be able to make more informed decisions about investment in drone technology in their respective organizations.

The present study has combined both the technology adoption model and the TPB and developed a theoretical model. The study enriches the literature on drone-based OFD services. Since users' acceptance of OFD services using drones is an under-researched area, the present study will make a meaningful contribution to bring the body of literature in this domain.

A quantitative theoretical model is proposed to measure how productivity performance can be affected by strategic decisions related to specific competitive priorities.

This study proposes the Primary Transformation Model (PTM) and an equation to measure cause-and-effect relationships between productivity and competitive priorities.

The interdependence between productivity and competitive priorities was studied using the PTM and the proposed model indicates that strategies that improve external performance also impact internal productivity. It was also observed that the compatibility between competitive priorities depends on the initial manufacturing conditions and the implementation method adopted.

The proposed model is theoretical and, as such, is an abstraction of reality and does not consider all possible aspects. It consists of a novel approach that still requires further empirical testing. The PTM provides insights about the trade-offs between productivity and strategic objectives, as well, contributes to the ongoing research on manufacturing strategy and can be further developed in future studies.

The main practical implication is to allow companies to relate their strategic decisions to their productivity performance.

This research also contributes to societal issues by enabling firms to better align strategic objectives and operations, which ultimately allows offering products more suited to the needs of customers, thus making better use of the required resources and favoring economic growth.

The model proposed allows objective assessment of actions aiming at operational efficiency and effectiveness, in addition to providing insights into cause-and-effect relationships between productivity and competitive priorities. The model can also be used in empirical investigations on manufacturing strategy.

The COVID-19 pandemic has resulted in a brand-new phenomenon in customer consumption patterns. This resulted from heightened health awareness brought on by the COVID-19 epidemic. There is a dearth of appropriate health psychology perspectives in the existing study examining the effect of COVID-19 on consumers’ use of crowdsourced logistics (CL) platforms. In order to provide unique and thorough insights into how consumer health concerns can affect consumers’ subjective views and their decisions to use CL, this study combines the health belief model and the technology acceptance model.

Five hundred valid responses from an online survey that was created and administered in Singapore were analysed using structural equation modelling.

The findings show that all of the suggested constructs have a favourable influence on consumers’ intentions to use CL. The suggested model also demonstrates high explanatory power, with perceived usefulness serving as the primary driver, followed by perceived ease of use and self-efficacy.

The study advances previous academic research on CL and offers guidance to CL companies and lawmakers for promoting sustainable and secured last-mile delivery.

The purpose of this study is to test the impact of time and price sensitivity on consumer satisfaction and purchase intention on online-to-offline (O2O) takeout platforms and explore the moderating effect of purchase preference on time sensitivity and satisfaction, as well as price sensitivity and satisfaction, in order to guide market pricing.

A structural equation model (SEM) of customer purchase intention was constructed, and the relationships between the variables (time sensitivity, price sensitivity, satisfaction and purchase intention) were examined. The completed questionnaires of 349 respondents were collected from the Questionnaire Star platform in China. The research model and hypotheses were then tested. Analytic hierarchy procedure was used to determine the moderating effect of purchase preference. Finally, the study proposes a pricing strategy for customer-active selective services.

Satisfaction positively influences purchase intention, and price sensitivity significantly increases satisfaction and further increases purchase intention; however, time sensitivity negatively affects satisfaction. Specifically, purchase preference has strongly moderated the relationship between time, price sensitivity and satisfaction. In addition, the findings show that when purchase preference is high, the effect of price sensitivity on satisfaction is stronger, suggesting the importance of purchase preference in strengthening purchase intentions. The research work recommends a pricing strategy involving value-added pricing primarily for time-sensitive customers, which can help build a high-end brand image and reduce price competition. Reduced pricing is mainly for price-sensitive customers, which is conducive to stimulating consumption within a specific time. This pricing strategy is important for adjusting market sensitivity and flexibility.

This research provides new ideas for related disciplines and guidance for the differentiated pricing and promotion of takeout platforms, as well as a theoretical basis for the diversified development of takeout platforms, improvement of personalized service quality and enhancement of customer stickiness. This study fills gaps in the existing literature on the moderating effect of purchase preference on time sensitivity and satisfaction and price sensitivity and satisfaction.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This study aims to examine the linkages between digitalisation, public service delivery and corruption in Ghana using survey data from 121 respondents in Ghana. The authors also examine the mediating role public service delivery offers on corruption.

This study relied on the capability theory as its theoretical lens and partial least squares structural equation modelling (PLS-SEM) as the data analysis technique.

Results from the PLS-SEM analysis show that public service delivery significantly reduces corruption, whilst digitalisation does not. However, public service delivery significantly mediated the relationship between digitalisation and corruption.

This study’s limitation is that the data was collected from Ghana only. To enhance the generalisability of findings, future research could collect data from multiple countries. In addition, the study did not factor in the moderating effects of demographic variables such as information and communication technology (ICT) literacy. Future research could consider these variables, given the low ICT literacy level of individuals in developing countries. Finally, future researchers could triangulate results with interviews and focus groups to provide more value to the identified questionnaire-based data.

The findings of this study highlight the need for digitalisation to be included in Ghana’s national policy objectives and service delivery objectives. It is essential for the government to ensure broader public engagement with stakeholders, including citizens, to ensure that digitalisation goals are achieved. The study’s results indicate that digitalisation does not significantly influence corruption. This calls for the government of Ghana to consider raising the level of human capital for the successful planning and deployment of e-services. This includes raising citizen ICT literacy and adopting cutting-edge technology to fully realize the benefits of online services. Developing capabilities, e-government leadership, and public sector employees as enablers of online public services should go hand-in-hand. It is also important to build connected capacities in the country and enhance access to information and technology, along with increasing digital infrastructure.

To the best of the authors’ knowledge, this is the first study to examine and offer a dual perspective on the role of digitalisation on public service delivery and corruption whilst considering the mediating role public service delivery offers on corruption.

Omnichannel sales have provided new impetus for the development of catering merchants. The authors thus focus on how catering merchants should manage capacities at the ordering, production and delivery stages to meet customers’ needs in different channels under third-party platform delivery and merchant self-delivery. This is of great significance for the development of the omnichannel catering industry.

This paper formulates the capacity decisions of omnichannel catering merchants under the third-party platform delivery and merchant self-delivery mode. The authors mainly use queuing theory to analyze the queuing behavior of online and offline customers, and the impact of waiting time on customer shopping behavior. In addition, the authors also characterize the merchant’s capacity by the rate in queuing model.

The authors find that capacities at ordering stage and food production stage are composed of base capacities and safety capacities, but the delivery capacities only have the latter. And in the self-delivery mode, merchants can develop higher safety capacities by charging delivery fees. The authors prove that regardless of the delivery mode, omnichannel sales can bring higher profits to merchants by integrating demand.

The authors focus on analyzing the capacity management of omnichannel catering merchants at the ordering, production and delivery stages. And the authors also add the delivery process into the omnichannel for analysis, so as to solve the problem of capacity decision-making under different delivery modes. The management of delivery capacity and its impact on other stages’ capacities are not covered in other literature studies, which is one of the main innovations of this paper.

The coronavirus disease (COVID-19) has increased food delivery service demand, which generates massive amounts of solid waste, specifically plastic material. Therefore, this study aims to examine the determinants of consumers' intention to reuse food delivery containers (ITR) using the extended theory of planned behavior (TPB). Moral obligation was included as an antecedent, while behavioral expectation (BE) ahead of behavioral intention was an immediate predictor of consumers' pro-environmental behaviors.

The hypotheses were tested on 348 food delivery service users in Malaysia and analyzed using the partial least squares structural equation modeling (PLS-SEM).

The findings indicated that consumers' ITR is directly influenced by perceived behavioral control and attitude. Perceived behavioral control and attitude had a positive partial indirect effect on ITR through BE. Meanwhile, subjective norms and moral obligation had a positive full indirect effect on ITR through BE.

The findings can be directly applied to practical situations of food delivery companies and environmental protection organizations managing solid waste among food delivery services.

Understanding consumers' ITR could promote practical environmental sustainability. Practically, the study provides insights to the food delivery service industry, policymakers and relevant stakeholders to encourage consumer behavior change by reusing food delivery containers in line with Sustainable Development Goal 12.

The study enhances the existing literature by extending TPB with two psychological variables: moral obligation (independent variable) and BE (mediating variable). To the best of the authors' knowledge, this study is the first attempt to empirically investigate BE in consumers' pro-environmental behavioral intention in a high-context culture and developing economy. This study could benefit food and beverage merchants, food delivery companies, governments, non-governmental organizations and pro-environmental behavior researchers in this industry.

Drawing on the mSERVQUAL model and spillover theory, this study aims to examine the mechanism through which food-ordering mobile app service quality influences users’ mobile app satisfaction, food satisfaction and repurchase intentions.

Online surveys were completed by 1,000 customers who used a food-ordering mobile app to order fast food on the day they completed the online survey. Structural equation modelling was then used to examine the proposed mechanism.

Results showed that the effects of food-ordering mobile app service quality on customer satisfaction (i.e. mobile app satisfaction and food satisfaction) and repurchase intention varied widely across service quality dimensions. Mobile app service quality had significant spillover effects on food satisfaction and repurchase intention.

Online food-delivery platforms should find the results insightful to better design their food-ordering mobile app. The findings can also assist restaurateurs and mobile payment companies with supporting the whole online food delivery process.

Rather than examining online food delivery service quality based on the service delivery process in the during-consumption stage or the service outcomes in the post-consumption stage, this study focused on the service quality in the pre-consumption stage to highlight the important role of online food delivery mobile apps. From a longitudinal perspective, this study drew on the associate network theory to explain the spillover effect of mobile app satisfaction in the pre-consumption stage on food satisfaction in the during-consumption stage and repurchase intention in the post-consumption stage.