Asian Journal of Management Cases, Ahead of Print.
This case sheds light on the accomplishments and legacy of a Pakistani entrepreneur who rapidly established a business empire. Malik Riaz Hussain, the founder of Bahria Town, the largest privately held real estate development company in Pakistan, faced allegations of engaging in corrupt activities to sway the system in his favour. Additionally, he was actively engaged in philanthropic endeavours, frequently referring to Islamic principles of charitable giving. This case highlights the intricate and ambiguous nature of ethical conduct in business within a context where religious teachings hold significance despite the prevalent corruption problem.
The impact of perceived environmental corporate social responsibility on idea generation and idea implementation
Anti-price-gouging law is neither good nor bad in itself: a proposal of narrative numeric method for transdisciplinary social discourses
JTAER, Vol. 19, Pages 774-796: Order Distribution and Routing Optimization for Takeout Delivery under Drone–Rider Joint Delivery Mode
JTAER, Vol. 19, Pages 774-796: Order Distribution and Routing Optimization for Takeout Delivery under Drone–Rider Joint Delivery Mode
Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer19020041
Authors: Fuqiang Lu Runxue Jiang Hualing Bi Zhiyuan Gao
Order distribution and routing optimization of takeout delivery is a challenging research topic in the field of e-commerce. In this paper, we propose a drone–rider joint delivery mode with multi-distribution center collaboration for the problems of limited-service range, unreasonable distribution, high delivery cost, and tight time windows in the takeout delivery process. The model is constructed with the minimum delivery cost and the overall maximum customer satisfaction as the objective function, and a two-stage heuristic algorithm is designed to solve the model. In the first stage, Euclidean distance is used to classify customers into the regions belonging to different distribution centers, and the affinity propagation (AP) clustering algorithm is applied to allocate orders from different distribution centers. The second stage uses an improved tabu search algorithm for route optimization based on specifying the number of rider and drone calls. This paper takes China’s Ele.me and Meituan takeout as the reference object and uses the Solomon data set for research. The experimental results show that compared with the traditional rider delivery mode, the drone–rider joint delivery mode with multiple distribution center collaboration can effectively reduce the number of riders used, lower the delivery cost, and improve the overall customer satisfaction.
COVID-19, the Russia–Ukraine war and the connectedness between the U.S. and Chinese agricultural futures markets
Culturally mixed co-branding product framing in China: the role of cultural sensitivity, product quality, and purchase probability
The future of the labor force: higher cognition and more skills
JTAER, Vol. 19, Pages 743-773: Exploring Tourists’ Behavioral Patterns in Bali’s Top-Rated Destinations: Perception and Mobility
JTAER, Vol. 19, Pages 743-773: Exploring Tourists’ Behavioral Patterns in Bali’s Top-Rated Destinations: Perception and Mobility
Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer19020040
Authors: Dian Puteri Ramadhani Andry Alamsyah Mochamad Yudha Febrianta Lusiana Zulfa Amelia Damayanti
The tourism sector plays a crucial role in the global economy, encompassing both physical infrastructure and cultural engagement. Indonesia has a wide range of attractions and has experienced remarkable growth, with Bali as a notable example of this. With the rapid advancements in technology, travelers now have the freedom to explore independently, while online travel agencies (OTAs) serve as important resources. Reviews from tourists significantly impact the service quality and perception of destinations, and text mining is a valuable tool for extracting insights from unstructured review data. This research integrates multiclass text classification and a network analysis to uncover tourists’ behavioral patterns through their perceptions and movement. This study innovates beyond conventional sentiment and cognitive image analysis to the tourists’ perceptions of cognitive dimensions and explores the sentiment correlation between different cognitive dimensions. We find that destinations generally receive positive feedback, with 80.36% positive reviews, with natural attractions being the most positive aspect while infrastructure is the least positive aspect. We highlight that qualitative experiences do not always align with quantitative cost-effectiveness evaluations. Through a network analysis, we identify patterns in tourist mobility, highlighting three clusters of attractions that cater to diverse preferences. This research underscores the need for tourism destinations to strategically adapt to tourists’ varied expectations, enhancing their appeal and aligning their services with preferences to elevate destination competitiveness and increase tourist satisfaction.