R.G. van Anholt

Bio: R.G. van Anholt is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Optimizing Logistics Processes in Cash Supply Chains

Abstract: The logistics of banknotes and coins has gained great attention in the past few years. Cost-efficient and secure cash deliveries to automated teller machines (ATMs), bank branches, and retailers have become necessary as a result of the financial crisis, the decline in cash usage, and the increase of the intensity and violence of raids on ATMs and cash-intransit. This dissertation presents five distinct yet interrelated research studies that provide solutions for managing ATM inventories and cash deliveries in order to improve the cost-efficiency of cash supply chains, user satisfaction, and the security of cash logistics. Extensive field research is conducted to gain an understanding of how users and managers perceive ATM service quality. Quantitative research techniques are used to develop tools and statistical models based on field research findings. Intuitive heuristics and exact algorithms are developed to forecast cash demands, control cash inventories, and manage ATM deliveries in cash supply chains of several maturities. Substantial contributions to the theory and logistics of cash distribution are made by solving new problems in novel ways. In addition, by using real world data, a potential cost saving of 32.0 to 37.7 million euro per annum is identified through benchmarking the performances of newly developed models with the cash operations of the three largest commercial banks in the Netherlands.

Real-time performance measurement system for automated teller machines

Abstract: Performance measurement systems have proven to facilitate process improvement in the past decades in various markets and environments. The objective of this paper is to design a performance measurement system to actively control, monitor and improve performance of automated teller machines. In our real-time performance measurement system we apply different weights for different types of potential lost sales. We implement the measurement system in an ATM inventory management context and conduct discrete event simulation experiments to demonstrate its added value in terms of cost and service. We use data from Dutch commercial banks in our performance and sensitivity analyses. Exhaustive numerical validation demonstrates that the implementation of our performance measurement system leads to a higher fill rate -- 99% instead of 98% -- with equal expenses, or a 3.7% cost reduction while maintaining an equal fill rate.

Atm'lerdekí nakíte yönelík talep tahmíní üzeríne sístematík yazin analízí

Abstract: Otomatik Vezne Makineleri, yaygin kullanilan ismi ile ATMler, bankacilik sektorunun en onemli servis kollarindan birini olusturmaktadir. Ozellikle COVID-19 surecinde, bankalar bircok sube ici islemi bu makinelere kaydirmis, para cekme ve yatirma limitleri arttirilarak bu temassiz servis noktasinin kullanimini tesvik etmistir. Bu makinelerde gerceklesen nakit akislarina yonelik yapilan talep tahminleri, herhangi bir urunden ziyade direk olarak nakit parayi hedef aldiǧindan, katma deǧeri yuksek zorlu bir sureci olusturmakla beraber;problemin karsit amaclarini ise, yeterli miktarda nakit bulunmamasi durumunda musteri ihtiyacinin giderilememesi ve buna karsilik makine icerisindeki paranin banka tarafindan herhangi bir yatirim aracinda deǧerlendirilmemesi olusturmaktadir. Bu calisma kapsaminda, gunumuze kadar ATM talep tahmini uzerine yapilmis calismalar, veri yapisi, tahmin yontemi, karsilasilan sikintilar, alternatif modeller, tahmin donemi gibi cesitli basliklarda siniflandirilmakta, henuz deǧinilmemis noktalar belirtilerek bundan sonraki calismalara zemin hazirlanmaktadir. Ozellikle talep tahmininde makine oǧrenmesi yontemlerinin yaygin olarak kullanildiǧi ve bu yontemlerin sonuclarinin istatistiksel tahmin yontemleri ciktilari ile karsilastirildiǧi tespit edilmistir. Calismalarin buyuk bir coǧunluǧu ortak bir acik veri seti kullanmakta ve karsilastirilabilir sonuclar sunmaktadir. Bildiǧimiz kadari ile bu calisma, tasvir ettiǧimiz alanda yapilan ilk yazin taramasi olmakta, ayni zamanda ulkemizde henuz uzerinde durulmamis bir alani isaret etmektedir. Amac: ATMlerle ilgili mevcut talep tahmini yazinin taranmasi, siniflandirilmasi ve bu alandaki calismalar icin yol haritasi olusturmasi. Yontem: Sistematik yayin taramasi, makalelerin siniflandirilmasi, kriterlerinin secilmesi ve buna gore siniflandirilip analiz edilmesi. Bulgular: ATM talep tahmini alaninda 32 calismanin varliǧi, ortak acik veri setlerinin kullanildiǧi, yaygin olarak makine oǧrenme metotlarinin uygulandiǧi ve istatistiksel talep tahmin modellerinin karsilastirma olcutu olarak sunulduǧunun tespiti. Ozgunluk: Bu alanda yapilan ilk sistematik yazin taramasi ve analizi olmasi.Alternate abstract:Automated Teller Machines, ATM's, constitute one of the most important service branches of the banking sector. During COVID-19, banks shifted many in-branch transactions to these machines and encouraged the use of this contactless service point by increasing the deposit and withdrawal limits. Demand forecasts for cash flows in these machines create a challenging process with high added value as they target cash directly. The contradictory objectives of the problem are that if the cash is not available, the customer need cannot be met, but the stocked money may not evaluated in any investment instrument. Within the scope of this study, the studies on ATM demand forecasting are classified under various topics such as data structure, forecasting method, alternative models, forecasting horizon, and the backgrounds for future studies are prepared by stating untouched points. Especially, it has been observed that machine learning methods are widely used in the literature and their results are compared with the outcomes of the statistical forecasting techniques. Most of the studies employ a common public data set and provide comparable results. To the best of our knowledge, this study is the first literature review in this field, and also marks an area that has not been addressed yet in our country. Purpose: Review of the literature relevant to the ATMs forecasting studies, their classification and providing a roadmap for further studies in this area. Method: Systematic literature review, classification of the articles, selection of the criteria and analyze by the selected criteria. Findings: Presence of 32 papers on the ATM forecasti g literature, employ of the common public data sets, widely utilization of the machine learning models, and detection of the use of statistical forecasting model results as the benchmark values. Originality: Being the first systematic review and analysis article on this area.