What Is the Level of People’s Acceptance for Electric Taxis and Buses? Exploring Citizens’ Perceptions of Transportation Electrification to Pay Additional Fees

Electric vehicles (EVs) are gradually addressing the environmental problem in cities created by internal combustion vehicles. However, to be widely used, a major challenge will still have to be tackled. Some significant challenges are the resistance to new technologies and EVs’ purchase cost, which is significantly higher than that of internal combustion vehicles. These challenges are similar to the adoption of EVs for public transportation, such as buses and taxis. Thus, this paper proposes valuable insights into attitudes and preferences for taxi and bus users for the willingness to travel in EVs, by performing a convenience sampling, focusing especially on young users. Moreover, this study highlights the possibility of the users paying additional fees to travel in electric taxis (ETs) or electric buses (EBs). Pearson’s chi-squared analysis was also performed to validate the hypotheses.

Total Cost of Ownership analysis and energy efficiency of electric, hybrid and conventional urban buses

From an economic perspective, the purchase cost of an electric bus is greater than that of a conventional one. This results from the additional components of the bus drivetrain and the costly charging infrastructure. However, it should be noted that electric bus ensures greener and more sustainable public transport. The presented study focuses on the economic and energy efficiency analysis of city buses with different types of driving system evaluated for selected urban and suburban routes. The routes differ in terms of the number of journeys per day, elevation, the daily distance travelled, and the daily operating time. The results demonstrate that driving conditions can affect economic efficiency. The Total Cost of Ownership (TCO) method used in the study shows that electric buses represent the highest TCO values among the vehicles taken into account. However, for the TCO calculated for electric and hybrid buses, fuel (energy) costs have a much lower share than for the TCO of conventional buses.

Model of Choice Photovoltaic Panels Considering Customers’ Expectations

Photovoltaic electricity generation is key to achieving deep decarbonization with a high degree of electrification. It is predicted that the energy sector will reduce carbon dioxide by producing electricity mainly from photovoltaic (PV) power. Although dynamic development of the implementation of photovoltaic panels has been observed, their choice considering customer specificity is still a problem. Therefore, the purpose of this study is to propose the model of choice photovoltaic panels considering customers’ expectations. It can support the choice of a photovoltaic panel of a certain quality (satisfaction of concrete customer) in combination with the cost of its purchase. The proposed model includes acquiring and then processing customers’ expectations into technical criteria, while simultaneously considering the weighting of these criteria. It is realized in a standardized way, i.e., the zero-unitarization method (MUZ), after which normalized values of the quality of the photovoltaic panels’ criteria are obtained. In turn, the quality of these products is estimated by the weighted sum model (WSM) and then integrated with purchase cost in qualitative cost analysis (AKJ). As a result, using the scale of relative states, it is possible to categorize customer satisfaction from indicating qualitative cost and selecting the photovoltaic panel expected by customers (the most satisfactory). The effectiveness of the model was demonstrated by a sensitivity analysis, after which the key PV criteria were indicated. The proposed model is intended for any entity who selects a photovoltaic panel for customers. The computerization of calculations may contribute to its utilitarian dissemination.

RESALE OF GREEN HOUSING COMPENSATES FOR ITS PREMIUM PRICING: AN EMPIRICAL STUDY OF CHINA

ABSTRACT Green housing reduces resource consumption and protects the ecological environment. Sustainable buildings and construction have gained increasing attention in the last decade. Many empirical studies have confirmed that green housing imposes a price premium at the presale stage. The high price could be a concern that prevents homebuyers from purchasing green buildings. However, there is a lack of empirical evidence on whether the premium pricing could be compensated for by the resale price. To address this gap, this study establishes a hedonic regression model to estimate the price premium of green housing at the resale stage. The results show that green housing certified with the Chinese Green Building Label (CGBL) offers a 6% price premium compared with non-green housing at the resale stage. The results also show that green housing with a higher level of green certification, e.g., the 3-star CGBL, provides a greater price premium at resale. The findings indicate that home-buyers can obtain financial compensation for the high cost when purchasing a green home. Our findings also indicate that the price premium for reselling a green home is not always enough to compensate for the purchase cost in different cities. Policy recommendations for government promotion of green housing are also discussed.

Replenishment Model with Entropic Order Quantity for Deteriorating Items under Inflation

The purpose of the current paper is to determine an optimal order quantity so as to minimize the total cost of the inventory system of a business enterprise. The model is developed for deteriorating items with stock and selling price dependent demand under inflation without permitting shortage. Optimal solution is achieved by cost minimization strategy considering replenishment cost, purchase cost, holding cost and deterioration cost with a special approach to entropy cost for bulk size purchasing units. The effectiveness of the proposed model has been avowed through empirical investigation. Sensitivity analysis has been accomplished to deduce managerial insights. Findings suggest that an increased inflationary effect results in increment in the system total cost. The paper can be extended by allowing shortage. The model can be utilized in the business firms dealing with bulk purchasing units of electric equipments, semiconductor devices, photographic films and many more.

A Multi Logistics Network Optimization Model of Power System based on Stochastic Demand and Inventory Decision

According to the disposal demand for packets and all kinds of constraints in the current condition, this paper discusses a modeling method of extended double-layer capacitated arc routing problems with Capacitated Arc Routing Problem (CARP) optimization model based on express logistics. The model is described in detail, and the solution of the model is discussed. The paper analyses and discusses the solution to complexity of the model, and proposes a better solution to the double-layer CARP optimization model. According to the scheme, the paper chooses a sort of improved ant colony algorithm to solve the model. And the results show that the scheme is beneficial to controlling the cost of logistics links, to minimizing purchase cost, transportation cost and delivery time. The scheme plays a very imperative role in enhancing the competitiveness of enterprises

Understanding the key takeaway of construction robots towards construction automation

PurposeThe construction industry is the major sector in China but it has been exposed to a series of problems including low productivity and workforce shortage. However, construction robots as an effective and sustainable approach to overcome the difficulties in construction industry have not been widely adopted. Few studies attempted to investigate on the adoption of construction robots in China. In order to fill this gap, this study aim to address the barriers to the adoption of construction robots in China.Design/methodology/approachThrough literature review, semi-structured interview 24 factors hindering the adoption of construction robots are summarized. Next, a total of valid 150 questionnaires delivered to the 7 stakeholders were collected. Ranking analysis was used to identify 21 critical factors was determined by the mean score analysis and factor analysis extracted 21 critical factors into 5 clusters.FindingsResults indicate that the “technological performance and management” cluster is the most dominant of the 5 clusters. The most important barrier is “Limited research and design input”, followed by “High purchase cost” and “Unstructured construction environment”. Construction robots are still under R&D have had limited field applications in the production and construction process.Originality/valueThe research findings provide a useful reference for different stakeholders to identify the critical factors appropriate strategies to promote the adoption of construction robots. Furthermore, this study provides recommendations to promote adoption of construction robots.

Exploiting the Chain Convenience Store Supplier Selection Based on ANP-MOP Model

The purchase cost of chain convenience stores accounts for a large proportion of the total cost. Enterprises are facing the problem of how to reasonably reduce the purchase cost while ensuring the quality of service. This paper first considers the uniqueness of chain convenience stores, draws on existing research results, and establishes an evaluation index system for chain convenience store suppliers through field research. Then, we use the principal component analysis method of selection to determine the weight of each index and make a preliminary ranking of the importance of chain convenience store suppliers. Secondly, according to the relevant weights determined by the network hierarchy method, the collected data are substituted into the multiobjective mathematical programming model to analyze the distribution of supplier procurement and calculate the procurement cost. The level of procurement expenditures accounted for by suppliers confirms the importance of suppliers. The results show that through the evaluation and ranking of suppliers and the effective management of suppliers according to the ranking results, not only the goal of cost minimization is achieved but also the reasonable service level is guaranteed, which is scientific.

Penentuan Sistem Pengadaan Bahan Baku Utama Berbasis Kontrak pada Perusahaan Roti dan Kue-Kue ANDALAS

Micro, small and medium enterprises (MSME) are striving to maximize profits through cost’s reduction while maintaining their product qualities and their customer’s satisfaction. ANDALAS is an MSME producing cakes and breads that intuitively purchase its raw material which results in a relatively high purchase cost. We propose a contract-based system using a linear programming approach to manage the purchasing activities of main ingredients. A mathematical model is proposed supporting the purchasing decisions which includes constraints such as: minimum purchase, safety stock, warehouse capacity, and demand’s requirements. The resulting model provides an improvement of 6,30% reduction in purchase costs. The improvement for each ingredient ranges from 4% to 16% where Eggs, Flour, Maizena, Margarine, Butter and Sugar are contractually ordered from one main supplier.

Operation policy of multi-capacity logistic robots in hotel industry

Purpose This paper aims to propose an operation policy of multi-capacity room service robots traveling within a hotel. As multi-capacity robots can serve many requests in a single trip, improved operation policy can reduce the investment cost of robots. Design/methodology/approach Using a mathematical model-based optimization technique, an optimal set of robots with minimum installation cost is derived while serving the entire room service demands. Through testing a variety of scenarios by changing the price and function of robots to be installed, insights that consider the various situations are offered. Findings Though the increase in capacity saves much time for room service at a lower capacity level, the amount of time saved gradually decreases as the capacity increases. Besides, the installation strategy is divided into two cases depending on the purchase cost of robots. Research limitations/implications Currently, the studies focusing on the adoption of service robots from an operations view are rarely be found. To reduce the burden of investment cost, this study takes the unique approach to improve the operation policy of service robots by using the multi-capacity robots. Practical implications This study guides the hotel to install an adequate set of robots. The result confirms that the optimal installation set of robots is affected by various factors, such as the room service information, the hotel structure and the unit execution cycle. Originality/value After the outbreak of COVID-19, people avoid face-to-face contact and interest in non-contact service is growing. This paper deals with the efficient way to implement non-contact delivery through logistic robots, a timely and important topic.