A new fuzzy multi-criteria decision-making approach for risk assessment of competitors’ cooperation in new product development projects

Purpose This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project. Design/methodology/approach New product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors. Findings Based on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors. Originality/value This paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.

Learning from experience in positioning new computer products

The correct positioning of new computer products has become crucially important as markets saturate and competition intensifies. The logistic function can provide an aid to product positioning. The method presented her addresses questions of price and performance only, and involves determination of learning curves from data on past successful product launches. It assumes that companies learn like individuals and that variables such as performance/price grow according to logistic curves limited by the basic technologies at hand.Digital's experience shows that its VAX family of computers is amenable to such an analysis, which also provides insights on the overall evolution of that technology. Besides offering guidelines for product positioning, this approach provides a means for estimating price drops and/or performance enhancements necessitated from delays in product delivery.

Automatic delivery-scam prevention using Raspberry-Pi

The word ‘automatic’ is unavoidable in this modern technical era. Automation facilitates not only technical advancement and time reduction to several processes, but also provides protection in various aspects. Delivery scam is a commonly occurring crime and it has to be reduced. Product delivery is a long process which involves various people to ensure correct delivery to the customer, providing chances for scam to occur. This paper discusses on an automatic delivery-scam prevention system with the help of Raspberry-Pi controller. This system provides safety to the ordered goods by limiting the authorisation of opening the packages to company and the customer only. It assures the safe and correct delivery of the ordered product.

Analysis on security-related concerns of unmanned aerial vehicle: attacks, limitations, and recommendations

<abstract> <p>Over time, the use of UAVs (unmanned aerial vehicles)/drones has increased across several civil and military application domains. Such domains include real-time monitoring, remote sensing, wireless coverage in disaster areas, search and rescue, product delivery, surveillance, security, agriculture, civil infrastructure inspection, and the like. This rapid growth is opening doors to numerous opportunities and conveniences in everyday life. On the other hand, security and privacy concerns for unmanned aerial vehicles/drones are progressively increasing. With limited standardization and regulation of unmanned aerial vehicles/drones, security and privacy concerns are growing. This paper presents a brief analysis of unmanned aerial vehicle's/drones security and privacy-related concerns. The paper also presents countermeasures and recommendations to address such concerns. While laying out a brief survey of unmanned aerial vehicles/drones, the paper also provides readers with up-to-date information on existing regulations, classification, architecture, and communication methods. It also discusses application areas, vulnerabilities, existing countermeasures against different attacks, and related limitations. In the end, the paper concludes with a discussion on open research areas and recommendations on how the security and privacy of unmanned aerial vehicles can be improved.</p> </abstract>

Exploring Purchase Intention using Delivery Services Apps during Covid-19 Pandemic among Malaysian Households

Online services of product delivery apps are more critical than ever. The COVID-19 pandemic has irrevocably altered internet purchasing habits. Customers are getting comfortable using the apps for services to order and do the shopping via their smartphone using the apps. The pandemic has quickened the transition to a more digital world. However, the debate remains as to what elements influence customers' purchase intentions toward using Delivery Services Apps (DSA). This research is therefore carried out to examine the key factors affecting the intention of customers to use delivery services apps among household customers in Malaysia during Covid-19 in 2020 to 2021. The research explored the most significant factors that influence the customer purchase intention on using DSA. There are 4 independent variables which we are focusing on: time factor (TF), price factor (PF), and convenience motivation factor (CMF) and product illustration factor (PIF). From the research, we have found out that convenience motivation factor is the most important exogenous variable that can influence purchase intention directly, sequentially through shopping motivations. The other factors that have a significant impact on a customer's purchase intentions are price factor and time factors. The least important factor that influences a customer’s purchase intention is the product illustrations. The study is carried out by gathering responses from over 167 participants in Malaysia. The objective of the study is to examine the use of online delivery services apps (DSA) to run the businesses efficiently and more effectively in order to attract household customer’s purchase intention. The novelty of this study is by giving the strategies and opportunities to the online business entrepreneurs to enhance and boost their sales by using social media as a platform of online delivery services apps to the community.

Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh

The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. The equipped camera module captures the road image and transfers it to the computer via socket server programming. The raspberry pi sends the camera image and waits for the steering angle value. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. Based upon this direction, L298 decides either forward or left or right or backwards movement. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. After that, Folium is used to depict the geographical location. Moreover, the system’s infrastructure is far too low-cost and easy to install.

Optimasi Rute Distribusi Menggunakan Metode Tabu Search Perusahaan Daerah Air Minum (PDAM) Tirta Bangun Kulon Progo

Logistics management is known as distribution and transportation management, while others call it physical distribution management. Distribution activities are very important for companies to deliver a product to consumers across various regions. The Regional Drinking Water Company (PDAM) Tirta Binangun Kulon Progo is one of the companies that produce Bottled Drinking Water (AMDK) under the product name AirKu. The high demand for AMDK AirKu products in 240 ml cup packaging was causing limited vehicles and the absence of a clear standard distribution route, which caused the distribution process to be carried out randomly. Therefore, to overcome the company's problems, it is possible to determine the Vehicle Routing Problem (VRP) route with the CVRP approach, where the route determination is based on fleet capacity. The method used was tabu search using the MATLAB application to minimize the bottled product delivery route traveled. The results obtained were the total distance traveled by 284.9 km. The proposed route had a distance savings of 118.26 km, which is better than the company route.