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This paper aims to develop a multi-objective problem for scheduling the operations of trucks entering and exiting cross-docks where the number of unloaded or loaded products by trucks is fuzzy logistic. The first objective function minimizes the maximum time to receive the products. The second objective function minimizes the emission cost of trucks. Finally, the third objective function minimizes the number of trucks assigned to the entrance and exit doors.

Two steps are implemented to validate and modify the proposed model. In the first step, two random numerical examples in small dimensions were solved by GAMS software with min-max objective function as well as genetic algorithms (GA) and particle swarm optimization. In the second step, due to the increasing dimensions of the problem and computational complexity, the problem in question is part of the NP-Hard problem, and therefore multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment.

Therefore, non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are used to solve 30 random problems in high dimensions. Then, the algorithms were ranked using the TOPSIS method for each problem according to the results obtained from the evaluation criteria. The analysis of the results confirms the applicability of the proposed model and solution methods.

This paper proposes mathematical model of truck scheduling for a real problem, including cross-docks that play an essential role in supply chains, as they could reduce order delivery time, inventory holding costs and shipping costs. To solve the proposed multi-objective mathematical model, as the problem is NP-hard, multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment. Therefore, NSGA-II and NRGA are used to solve 30 random problems in high dimensions.

Driven by sustainable production, mobile robots are introduced as a new clean-energy material handling tool for mixed-model assembly lines (MMALs), which reduces energy consumption and lineside inventory of workstations (LSI). Nevertheless, the previous part feeding scheduling method was designed for conventional material handling tools without considering the flexible spatial layout of the robotic mobile fulfillment system (RMFS). To fill this gap, this paper focuses on a greening mobile robot part feeding scheduling problem with Just-In-Time (JIT) considerations, where the layout and number of pods can be adjusted.

A novel hybrid-load pod (HL-pod) and mobile robot are proposed to carry out part feeding tasks between material supermarkets and assembly lines. A bi-objective mixed-integer programming model is formulated to minimize both total energy consumption and LSI, aligning with environmental and sustainable JIT goals. Due to the NP-hard nature of the proposed problem, a chaotic differential evolution algorithm for multi-objective optimization based on iterated local search (CDEMIL) algorithm is presented. The effectiveness of the proposed algorithm is verified by dealing with the HL-pod-based greening part feeding scheduling problem in different problem scales and compared to two benchmark algorithms. Managerial insights analyses are conducted to implement the HL-pod strategy.

The CDEMIL algorithm's ability to produce Pareto fronts for different problem scales confirms its effectiveness and feasibility. Computational results show that the proposed algorithm outperforms the other two compared algorithms regarding solution quality and convergence speed. Additionally, the results indicate that the HL-pod performs better than adopting a single type of pod.

This study proposes an innovative solution to the scheduling problem for efficient JIT part feeding using RMFS and HL-pods in automobile MMALs. It considers both the layout and number of pods, ensuring a sustainable and environmental-friendly approach to production.

The research aims to provide a nuanced understanding of the complex social, psychological and organizational factors that serve as the foundation driving academics' knowledge-sharing behavior (KSB) within an academic enclave.

A cross-sectional research design using the partial least squares structural equation modeling (PLS-SEM) approach was employed to examine the determinants of personality traits among tertiary academics in Malaysia in relation to their KSB. To this end, a self-administered survey was distributed to a sample group of 526 respondents.

It is evident that conscientiousness and agreeableness are the personality traits that play a significant role in promoting KSB among academics in higher learning institutions (HLIs). These personality traits are positively linked with academics' willingness to transfer and receive knowledge. In contrast, the personality trait of openness to experience does not significantly influence KSB.

This study has employed a four-item measurement for evaluating the three distinct personality traits. Despite employing a brief measurement tool, the study has demonstrated significant reliability and validity, particularly in terms of convergent and discriminant validity.

The present study has revealed that conscientiousness in academics is intimately linked with their KSB, which is of paramount importance in the output-based education system. Notably, agreeableness among academics also conveys a positive effect on knowledge sharing (KS) in HLIs, as it cultivates trust and helpfulness among individuals and facilitates the exchange of valuable tacit knowledge.

This research explores the relationship between personality traits and KSB among Malaysian academics in HLIs. The study adopts the theories of planned behavior (TPB) and social capital theory (SCT) as theoretical ground, providing a nuanced understanding of the underlying motivations and mechanisms driving academics' knowledge-sharing behavior within the unique socio-cultural context of Southeast Asia.

With the rapid development of the sharing economy in manufacturing industries, manufacturers and the equipment suppliers frequently share capacity through the third-party platform. This paper aims to study influences of manufacturers sharing capacity on the supplier and to analyze whether the supplier shares capacity as well as its influences.

This paper deals with conditions that the supplier and manufacturers share capacity through the third-party platform, and the third-party platform competes with the supplier in equipment sales. Considering the heterogeneity of the manufacturer's earning of unit capacity usage and the production efficiency of manufacturer's usage strategies, this paper constructs capacity sharing game models. Then, model equilibrium results under different sharing scenarios are compared.

The results show that when the production or maintenance cost is high, manufacturers sharing capacity simultaneously benefits the supplier, the third-party platform and manufacturers with high earnings of unit capacity usage. When both the rental efficiency and the production cost are low, or both the rental efficiency and the production cost are high, the supplier simultaneously sells equipment and shares capacity. The supplier only sells equipment in other cases. When both the rental efficiency and the production cost are low, the supplier’s sharing capacity realizes the win-win-win situation for the supplier, the third-party platform and manufacturers with moderate earnings of unit capacity usage.

This paper innovatively examines supplier's selling and sharing decisions considering manufacturers sharing capacity. It extends the research on capacity sharing and is important to supplier's operational decisions.

Collaborative Logistics (CL) and merging operations are crucial strategies for reducing costs and improving service in transportation companies. This study proposes a model for optimizing efficiency in supply chain networks through inbound and outbound Collaborative Logistics implementation among the carriers in centralized, coordinated networks with cross-docking.

A mixed-integer non-linear programming model is developed to determine the optimal truck-goods assignment while gaining economies of scale through mixing multiple less-than-truckload (LTL) products with different weight-to-volume ratios. Unlike the previous studies that have considered Collaborative Logistics from the cost and profit-sharing perspective, the proposed model seeks to determine an appropriate form of Collaborative Logistics in the VRP.

This article shows that in a three-echelon supply chain consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. This approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of collaborative logistics among the carriers was discussed. In a three-echelon SC consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. Using a combination of experimental analysis and optimization process, it was recommended that managers be cautious that too much (full or complete) or no collaboration can result in SC performance deterioration.

The suggested approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of Collaborative Logistics among the carriers was discussed.

The main purpose of this study is to fill the research gap on how B2B global service firms integrate dynamic capabilities within their omnichannel management to influence positive word of mouth (WOM), customer engagement (CE) and customer equity.

Drawing on the dynamic capability and WOM theories, a model has been developed that defines the subjects of the empirical test. The paper reports on data collected from 312 service-oriented global firms in Australia, through a cross-sectional survey. Data were analyzed using structural equation modeling.

The findings suggest that content management (i.e. information consistency, source trustworthiness and endorsement) and concerns management (i.e. privacy, security and recovery) capabilities are the two significant antecedents of positive WOM within a B2B omnichannel setting in international marketing. The findings also confirm the key mediating role of CE between positive WOM and customer equity.

The findings extend dynamic capability theory in the context of international marketing by linking WOM, CE and customer equity. The findings add further theoretical rigor by establishing the nomological chain between positive WOM and customer equity, in which CE plays a key mediating role.

Gastronomic festivals are important events to bring people together around food-themed activities. This study aimed at determining the relationships between festival quality, memorable food experience, loyalty, behavioral intention, hedonic well-being, and eudaimonic well-being. In this study, festival quality is the independent variable that affects the memorable food experience, the memorable food experience is the independent variable that affects loyalty, and loyalty is the independent variable that affects behavioral intent. Hedonic well-being and eudaimonic well-being are moderating variables. Behavioral intention is the dependent variable, while memorable food experience and loyalty are both dependent and independent variables.

The population consisted of local tourists visiting Orange Blossom Carnival held in Adana, Turkey. The survey technique and the convenience sampling method were preferred and 545 data were obtained.

The analysis results showed that all dimensions of the memorable food experience are strongly affected by festival quality. Plus, superior service approach and high value perception dimensions of the memorable food experience have significant effects on loyalty. Furthermore, destination loyalty was found to have a strong effect on behavioral intentions. Moreover, higher levels of Hedonic well-being (HWB) and Eudomenic well-being (EWB) were found to increase the effect of loyalty on behavioral intention; accordingly, the moderator roles of HWB and EWB were determined.

This article provides information that the memorable dining experiences of festival visitors who attend the Orange Blossom Carnival in Adana affect the quality of the festival and their intentions to loyalty. In addition, in the study, it was found that the well-being of carnival visitors had a moderating role in the effect of their loyalty on their behavioral intentions. Therefore, this article provides information on how the food experiences and well-being of the visitors at the gastronomy festival will affect which factors.

According to the findings, gastronomy-based events may affect tourists’ experiences, and tourists’ psychological well-being affects loyalty and behavioral intentions. Destination management organizations can learn about gastronomy-based festivals. The results of the study include a number of theoretical and practical findings for destination management organizations, festival managers, policy makers and academics working in the literature.

Using the Stimulus-Organism-Response (SOR) model as a theoretical guide, this study employed a conceptual model involving residents’ place attachment (S) to the destination in which they live and emotional solidarity with tourists (O) as precursors to their involvement in tourism (R). The purpose of this paper is threefold: To determine (1) whether residents’ place attachment explains their emotional solidarity with tourists, (2) if emotional solidarity is an effective predictor of residents’ involvement in tourism planning and development and (3) if emotional solidarity dimensions mediate the relationship between place attachment and involvement.

Data were collected from 378 permanent resident heads of households living in, or adjacent to, central Orlando, using a self-administered survey with a census-guided systematic sampling method. Data were subjected to tests of normality and common method bias, followed by a two-step confirmatory factor analysis and structural equation modeling.

Seven of the 11 proposed model hypotheses were supported, with moderate variances explained in each of the four outcome variables: welcoming nature (R² = 19.3%), emotional closeness (R² = 24.5%), sympathetic understanding (R² = 39.4%) and involvement (R² = 36.8%). Though both place identity and place dependence (as two dimensions of place attachment) were partial mediators, the former proved to be more pronounced.

This study employed non-economic measures—place attachment and emotional solidarity—in determining residents’ involvement in tourism within their community. Such an approach provides fresh insights into how such symbolic constructs can contribute to residents’ positive, actionable involvement in tourism. This research is one of the few that have incorporated emotional solidarity as a construct within the SOR model and the first to examine the indirect effects (through mediation) of emotional solidarity.

Consumer-perceived review attitude determines consumer overall information adoption and is a core part of consumer’s online-shopping. This study aims to focus on factors that could influence consumer review attitude and can be used by marketers to shape individual information perception.

The study used the questionnaire method to collect data from online shoppers and the modelling of structural equations as an empirical approach to analyse the data.

The findings demonstrate that both systematic and heuristic cues impact the reviewer’s credibility and perceived website attitude differently, which, in turn, influence review attitude. Review characteristics, such as factuality, consistency and relevancy, have a positive relationship with reviewer credibility, while only review consistency and relevancy appears to have a relationship with review attitude. Website characteristics such as reputation, familiarity and social interactivity positively influence the website attitude, which positively influences review attitude. Apart from this, review skepticism has a significant negative relationship with review attitude.

This study could help to foster a positive attitude towards online reviews. Digital marketers need to motivate trusted reviewers to post consistent, fact-based reviews. Further improving the overall website reputation and interactivity could bring a positive attitude towards the reviews. Also, digital marketers must filter and avoid contradictory reviews or reviews that have a bipolar message and reviews expressing numerous emotions to enhance review relevance and consistency.

The current study addresses the need to understand the formation of consumer review attitude through both review and website characteristics using heuristic – systematic model. The paper captures the complex process undergone by the consumer to decipher review attitude and thereby extend the understanding of consumer information processing.

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.