Electric Vehicle Assignment Considering Users’ Waiting Time

A one-way electric-car-sharing system is an environmentally friendly option for urban transportation systems, which can reduce air pollution and traffic congestion with effective vehicle assignment. However, electric vehicle assignment usually faces a dilemma where an insufficient battery level cannot fulfill the requests of users. It greatly affects assignment choices and order fulfillment rates, resulting in the loss of platform profit. In this study, with the assumption that the users agree to wait for a period of time during which electric vehicles can be charged to fulfill trip demands, we proposed a waiting-time policy and introduced users’ utility to measure user retention. Then, we set up a bi-level electric-vehicle assignment model with a waiting-time policy to optimize the assignment and waiting decisions. The numerical results show that under the waiting-time policy, we can achieve more profits, a higher trip fulfillment rate, and a significant improvement in vehicle utilization. It not only generates more profits for the platform but also provides a better service for users and lays a user foundation for the future development and operation.

Task scheduling for transport and pick robots in logistics: a comparative study on constructive heuristics

We study the Transport and Pick Robots Task Scheduling (TPS) problem, in which two teams of specialized robots, transport robots and pick robots, collaborate to execute multi-station order fulfillment tasks in logistic environments. The objective is to plan a collective time-extended task schedule with the minimization of makespan. However, for this recently formulated problem, it is still unclear how to obtain satisfying results efficiently. In this research, we design several constructive heuristics to solve this problem based on the introduced sequence models. Theoretically, we give time complexity analysis or feasibility guarantees of these heuristics; empirically, we evaluate the makespan performance criteria and computation time on designed dataset. Computational results demonstrate that coupled append heuristic works better for the most cases within reasonable computation time. Coupled heuristics work better than decoupled heuristics prominently on instances with relative few pick robot numbers and large work zones. The law of diminishing marginal utility is also observed concerning the overall system performance and different transport-pick robot numbers.

The Effect of Baby Food E-Store Image (for Ages 0–3) on Consumers’ Purchase Intention

This research aims to investigate the influence of baby food e-store image (for ages 0–3) on consumers’ purchase intention, mainly based on the stimulus-organism-response (S-O-R) model. Perceived value is additionally tested as a mediator of the relationship between baby food e-store image and consumers’ purchase intention. An online questionnaire survey was conducted among consumers of baby food e-stores that specialize in ages 0–3. The final sample comprised 584 valid responses. To test the hypotheses in the relationships among latent variables, structural equation model analysis was used in this study. The findings showed that design image, order fulfillment image, communication service image, and security image of baby food e-stores have positive effects on consumers’ perceived value, while perceived value mediates the relationship between baby food e-stores and consumers’ purchase intention. As a result, more perceived value would be created between online stores and their consumers with a higher level of value. Two managerial implications derived from this study explain how to manage baby food e-stores and how to promote online baby food undertakings. Particularly, consumers’ perceived emotional and functional value can be shaped by four dimensions of baby food e-store image, e-store design image, order fulfillment image, communication service image, and security image, which finally determines their purchase intentions. The originality and value of this study enriches the importance of consumers’ perceived value in the field of online store image. Moreover, this study demonstrates that baby food e-store image increases consumers’ perceived value and purchase intention.

Analisis Penjadwalan Produksi Berdasarkan Pesanan Menggunakan Metode Asas Prioritas pada CV Davero Cemerlang Indonesia Surabaya

The purpose of this study was to determine the most efficient order scheduling technique on CV. Davero Jaya Shining Indonesia to reduce delays in order fulfillment. The suggested scheduling approach is based on a priority rule system that includes the following criteria: first come, first served, lowest processing time, longest processing time, and earliest due date (first come first served). Davero Jaya Cemerlang Indonesia uses the SPT technique in its manufacturing process, according to their company CV. The company decided to adopt this technique because it seemed reasonable from a consumer's point of view. The downside of this technique is that it often causes delays in completing client orders. Based on the results of data analysis and debates that have been given, the FCFS technique is the most superior method among others. Considering the fact that the findings of the FCFS method effectiveness measure are consistent with the current criteria, which include minimum average completion scores, maximum utility, minimum average delay, and minimum average labor force in the system. Therefore, the researchers gave suggestions to the company CV. Davero Jaya Cemerlang Indonesia to use the FCFS method as an alternative production scheduling method. With the application of the FCFS method in CV. Davero Jaya Cemerlang Indonesia is expected to be able to help resolve production scheduling problems that have been happening so far. So that the problem of delays in completing orders can be minimized. Keywords: Scheduling, Gantt Chart, Priority Principles and CV. Davero Jaya Cemerlang Indonesia

An examination of the effects of omni-channel service offerings on retailer performance

PurposeBoth online and brick and mortar retailers have invested heavily in developing omni-channel service offerings. Though seen as a competitive necessity, these omni-channel service offerings increase costs and complexities. The purpose of this study is to examine the effects of strategies involving bundles of omni-channel services related to order fulfillment and returns management on retailer performance.Design/methodology/approachArchival data were obtained for 152 retailers and analyzed using ordinary least squares regression. Robustness tests using an alternative dependent variable and a model-based classification strategy corroborate our findings.FindingsRetailers offering full sets of high integration omni-channel services (buy online pick up in store, ship from store and in-store returns) have better performance (e.g. sales, growth and competitive position) and web sales than retailers that offer only a partial mix of these high integration services. Retailers offering a partial bundle of high integration services, in turn, have better performance and web sales than retailers that offer none of these services.Originality/valueThe research extends work that has examined the performance effects of omni-channel services on individual retailers. Our results indicate retailers benefit the most when offering a full set of high integration omni-channel services, suggesting retailers who have only adopted a subset of these services could improve performance through broader adoption of services. The results further indicate partial adoption of high integration services is better than no adoption.

ROLE OF ORDER FULFILLMENT ON THE PERFORMANCE OF MANUFACTURING FIRMS IN KENYA

Purpose: The main purpose of the study was determine role order fulfillment on performance of manufacturing firms in Kenya.Methodology: A descriptive research design was used. The target population of the study were managers or equivalent from Six (6) departments that is Procurement, finance, legal, stores, human resource and quality control because they are directly concerned with supply chain. The study adopted the use of a questionnaire and a document analysis as the main research instrument. The study adopted both quantitative and qualitative approaches, implying that both descriptive statistics and inferential statistics were employed. Quantitative data collected from the document analysis was analyzed statistically using the Statistical Package for Social Scientist (SPSS version 22). The study tested the significance level of each independent variable against the dependent variable at 95% confidence level using ANOVA, Correlation and regression techniques.Findings: The findings showed that order fulfillment has a positive and significant effect on firm performance, 0.723, p < 0.05.Unique contribution to theory, practice and policy: There is need to put in place review teams that constantly review the strategies with the view to improve them for increased effectiveness. Effective cost reduction mechanisms, combined with a well-structured organizational policy on procurement and supply chain management practices will eliminate the notion of having multiple suppliers to mitigate for unsatisfactory service.

Joint Product Framing (Display, Ranking, Pricing) and Order Fulfillment Under the Multinomial Logit Model for E-Commerce Retailers

Problem definition: We study a joint product framing and order fulfillment problem with both inventory and cardinality constraints faced by an e-commerce retailer. There is a finite selling horizon and no replenishment opportunity. In each period, the retailer needs to decide how to “frame” (i.e., display, rank, price) each product on his or her website as well as how to fulfill a new demand. Academic/practical relevance: E-commerce retail is known to suffer from thin profit margins. Using the data from a major U.S. retailer, we show that jointly planning product framing and order fulfillment can have a significant impact on online retailers’ profitability. This is a technically challenging problem as it involves both inventory and cardinality constraints. In this paper, we make progress toward resolving this challenge. Methodology: We use techniques such as randomized algorithms and graph-based algorithms to provide a tractable solution heuristic that we analyze through asymptotic analysis. Results: Our proposed randomized heuristic policy is based on the solution of a deterministic approximation to the stochastic control problem. The key challenge is in constructing a randomization scheme that is easy to implement and that guarantees the resulting policy is asymptotically optimal. We propose a novel two-step randomization scheme based on the idea of matrix decomposition and a rescaling argument. Managerial implications: Our numerical tests show that the proposed policy is very close to optimal, can be applied to large-scale problems in practice, and highlights the value of jointly optimizing product framing and order fulfillment decisions. When inventory across the network is imbalanced, the widespread practice of planning product framing without considering its impact on fulfillment can result in high shipping costs, regardless of the fulfillment policy used. Our proposed policy significantly reduces shipping costs by using product framing to manage demand so that it occurs close to the location of the inventory.

Fuzzy Multi-Criteria Decision-Making Approach for Online Food Delivery (OFD) Companies Evaluation and Selection: A Case Study in Vietnam

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper’s objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are “convenience of payment”, “delivery speed”, “online service level”, “order fulfillment”, and “delivery cost”. From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development.