Publications with Fulltext
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access A longitudinal analysis of customer satisfaction and share of wallet: investigating the moderating effect of customer characteristics(American Marketing Association (AMA), 2007) Cooil, B.; Keiningham, T. L.; Hsu, M.; Department of Business Administration; Aksoy, Lerzan; Faculty Member; Department of Business Administration; College of Administrative Sciences and EconomicsCustomer loyalty is an important strategic objective for all managers. Research has investigated the relationship between custom̀er satisfaction and loyalty in various contexts. However, these predominantly cross-sectional studies have focused on customer retention as the primary measure of loyalty. There has been little investigation into the impact on share of wallet. Using data from the Canadian banking industry, this research aims to (1) provide the first longitudinal examination of the impact of changes in customer satisfaction on changes in share of wallet and (2) determine the moderating effects of customer age, income, education, expertise, and length of relationship. Data from 4319 households using 12,249 observations over a five-year period indicate a positive relationship between changes in satisfaction and share of wallet. In particular, the initial satisfaction level and the conditional percentile of change in satisfaction significantly correspond to changes in share of wallet. Two variables, income and length of the relationship, negatively moderate this relationship. Other demographic and situational characteristics have no impact.Publication Open Access A longitudinal examination of net promoter and firm revenue growth(American Marketing Association (AMA), 2007) Keiningham, Timothy L.; Cooil, Bruce; Andreassen, Tor Wallin; Department of Business Administration; Aksoy, Lerzan; Faculty Member; Department of Business Administration; College of Administrative Sciences and EconomicsManagers have widely embraced and adopted the Net Promoter metric, which noted loyalty consultant Frederick Reichheld advocates as the single most reliable indicator of firm growth compared with other loyalty metrics, such as customer satisfaction and retention. Recently, however, there has been considerable debate about whether this metric is truly superior. This article (1) employs longitudinal data from 21 firms and 15,500-plus interviews from the Norwegian Customer Satisfaction Barometer to replicate the analyses used in Net Promoter research and (2) compares Reichheld and colleagues' findings with the American Customer Satisfaction Index. Using industries Reichheld cites as exemplars of Net Promoter, the research fails to replicate his assertions regarding the "clear superiority" of Net Promoter compared with other measures in those industries.Publication Open Access A machine learning approach for implementing data-driven production control policies(Taylor _ Francis, 2021) Department of Business Administration; N/A; Tan, Barış; Khayyati, Siamak; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 28600; N/AGiven the extensive data being collected in manufacturing systems, there is a need for developing a systematic method to implement data-driven production control policies. For an effective implementation, first, the relevant information sources must be selected. Then, a control policy that uses the real-time signals collected from these sources must be implemented. We analyse the production control policy implementation problem in three levels: choosing the information sources, forming clusters of information signals to be used by the policy and determining the optimal policy parameters. Due to the search-space size, a machine-learning-based framework is proposed. Using machine learning speeds up optimisation and allows utilising the collected data with simulation. Through two experiments, we show the effectiveness of this approach. In the first experiment, the problem of selecting the right machines and buffers for controlling the release of materials in a production/inventory system is considered. In the second experiment, the best dispatching policy based on the selected information sources is identified. We show that selecting the right information sources and controlling a production system based on the real-time signals from the selected sources with the right policy improve the system performance significantly. Furthermore, the proposed machine learning framework facilitates this task effectively.Publication Open Access A method for estimating stock-out-based substitution rates by using point-of-sale data(Taylor _ Francis, 2009) Öztürk, Ömer Cem; Department of Business Administration; Tan, Barış; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 38819Empirical studies in retailing suggest that stock-out rates are quite high in many product categories. Stock-outs result in demand spillover, or substitution, among items within a product category. Product assortment and inventory management decisions can be improved when the substitution rates are known. In this paper, a method is presented to estimate product substitution rates by using only Point-Of-Sale (POS) data. The approach clusters POS intervals into states where each state corresponds to a specific substitution scenario. Then available POS data for each state is consolidated and the substitution rates are estimated using the consolidated information. An extensive computational analysis of the proposed substitution rate estimation method is provided. The computational analysis and comparisons with an estimation method from the literature show that the proposed estimation method performs satisfactorily with limited information.Publication Open Access A multiperiod stochastic production planning and sourcing problem with service level constraints(Springer, 2005) Yıldırım, Işıl; Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; 3579We study a stochastic multiperiod production planning and sourcing problem of a manufacturer with a number of plants and/or subcontractors. Each source, i.e. each plant and subcontractor, has a different production cost, capacity, and lead time. The manufacturer has to meet the demand for different products according to the service level requirements set by its customers. The demand for each product in each period is random. We present a methodology that a manufacturer can utilize to make its production and sourcing decisions, i.e., to decide how much to produce, when to produce, where to produce, how much inventory to carry, etc. This methodology is based on a mathematical programming approach. The randomness in demand and related probabilistic service level constraints are integrated in a deterministic mathematical program by adding a number of additional linear constraints. Using a rolling horizon approach that solves the deterministic equivalent problem based on the available data at each time period yields an approximate solution to the original dynamic problem. We show that this approach yields the same result as the base stock policy for a single plant with stationary demand. For a system with dual sources, we show that the results obtained from solving the deterministic equivalent model on a rolling horizon gives similar results to a threshold subcontracting policy.Publication Open Access A preference-based, multi-unit auction for pricing and capacity allocation(Elsevier, 2018) Lessan, Javad; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819We study a pricing and allocation problem of a seller of multiple units of a homogeneous item, and present a semi-market mechanism in the form of an iterative ascending-bid auction. The auction elicits buyers' preferences over a set of options offered by the seller, and processes them with a random-priority assignment scheme to address buyers' "fairness" expectations. The auction's termination criterion is derived from a mixed-integer programming formulation of the preference-based capacity allocation problem. We show that the random priority- and preference-based assignment policy is a universally truthful mechanism which can also achieve a Pareto-efficient Nash equilibrium. Computational results demonstrate that the auction mechanism can extract a substantial portion of the centralized system's profit, indicating its effectiveness for a seller who needs to operate under the "fairness" constraint.Publication Open Access A threat to loyalty: fear of missing out (FOMO) leads to reluctance to repeat current experiences(Public Library of Science, 2020) Hayran, Ceren; Anık, Lalin; Department of Business Administration; Canlı, Zeynep Gürhan; Faculty Member; Department of Business Administration; Graduate School of Business; 16135We investigate a popular but underresearched concept, the fear of missing out (FOMO), on desirable experiences of which an individual is aware, but in which they do not partake. Through laboratory and field studies, we establish FOMO's pervasiveness as a psychological phenomenon, present real-life contexts wherein FOMO may be experienced, and explore its behavioral consequences. Specifically, we show that FOMO poses a threat to loyalty by decreasing one's intentions to repeat a current experience and may decrease the valuation of the current experience.Publication Open Access A transaction utility approach for bidding in second-price auctions(Elsevier, 2020) Akçay, Yalçın; Department of Business Administration; Sayman, Serdar; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 112222In both the Vickrey and eBay auctions, bidding the reservation price is the optimal strategy within the conventional utility framework. However, in practice, buyers tend to bid less than their reservation prices, and bid multiple times, thus increase their bids, in the course of an auction. In this paper, we show that both underbidding and multiple bidding behaviors can be consistent with utility maximization, if buyer's utility incorporates a transaction utility (reference price dependent) component. Transaction utility is based on the difference between the buyer's reference price and actual price paid; it captures the perceived value of the deal. More specifically, we show that the optimal bid is lower than the reservation price, but higher than the reference price. Furthermore, buyer may re-bid (above the prior optimal level) if the reference price is revised upon observing a higher current price.Publication Open Access A trilevel r-interdiction selective multi-depot vehicle routing problem with depot protection(Elsevier, 2020) Hesam Sadati, Mir Ehsan; Aras, Necati; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308The determination of critical facilities in supply chain networks has been attracting the interest of the Operations Research community. Critical facilities refer to structures including bridges, railways, train/metro stations, medical facilities, roads, warehouses, and power stations among others, which are vital to the functioning of the network. In this study we address a trilevel optimization problem for the protection of depots of utmost importance in a routing network against an intelligent adversary. We formulate the problem as a defender-attacker-defender game and refer to it as the trilevel r-interdiction selective multi-depot vehicle routing problem (3LRI-SMDVRP). The defender is the decision maker in the upper level problem (ULP) who picks u depots to protect among m existing ones. In the middle level problem (MLP), the attacker destroys r depots among the (m–u) unprotected ones to bring about the biggest disruption. Finally, in the lower level problem (LLP), the decision maker is again the defender who optimizes the vehicle routes and thereby selects which customers to visit and serve in the wake of the attack. All three levels have an identical objective function which is comprised of three components. (i) Operating or acquisition cost of the vehicles. (ii) Traveling cost incurred by the vehicles. (iii) Outsourcing cost due to unvisited customers. The defender aspires to minimize this objective function while the attacker tries to maximize it. As a solution approach to this trilevel discrete optimization problem, we resort to a smart exhaustive enumeration in the ULP and MLP. For the LLP we design a metaheuristic algorithm that hybridizes Variable Neighborhood Descent and Tabu Search techniques adapted to the Selective MDVRP (SMDVRP). The performance of this algorithm is demonstrated on 33 MDVRP benchmark instances existing in the literature and 41 SMDVRP instances generated from them. Numerical experiments on a large number of 3LRI-SMDVRP instances attest that our comprehensive method is effective in dealing with the defender-attacker-defender game on multi-depot routing networks.Publication Open Access Advance care plans: planning for critical healthcare decisions(The University of Chicago Press, 2022) Botti, Simona; Morwitz, Vicki G.; Department of Business Administration; Okutur, Nazlı Gürdamar; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 353043Advance care plans (ACPs) document personal values and healthcare preferences for critical situations where individuals cannot speak for themselves. Although ACPs can prevent receiving costly unwanted treatments and ensure receiving preferred treatments, few people have one. We examine factors associated with ACP engagement and design interventions to increase engagement. We find that ACP holders and nonholders largely have common values and preferences, which similarly vary with demographics. For example, older (vs. younger) individuals, regardless of ACP ownership, prefer to be able to care for themselves and to avoid prolonged end-of-life medical interventions. These two groups also differ in important ways: those who have or intend to create ACPs (vs. not) prefer avoiding invasive life-sustaining treatments and having a peaceful end of life. However, interventions that use these similarities and differences to increase ACP engagement are unsuccessful. We propose that structural approaches may be more effective in increasing ACP uptake.Publication Open Access An empirical analysis of the main drivers affecting the buyer surplus in E-auctions(Taylor _ Francis, 2018) Department of Business Administration; Department of Industrial Engineering; Karabağ, Oktay; Tan, Barış; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; N/A; 28600We empirically examine the impacts of the product category, the auction format, the 2008 global financial crisis, the group purchasing, the contract type, the platform ownership, and the number of participating suppliers on the buyer surplus obtained from e-auctions. To this end, we collect a unique dataset from a purchasing organisation that offers e-auction solutions to its corporate customers. By using a standard Tobit model, we show that the product categories, the auction type, and the number of participating suppliers have significant effects on the decrease in the procurement prices with respect to the minimum of the initial submitted bids. It is observed that the 2008 global financial crisis led to an increase in the buyer surplus. We classify the product categories into three groups based on their impacts on the average of the decrease in the procurement prices. We show that the average decrease in procurement prices is higher for the group purchasing option than for the individual buying option. It is concluded that the types of contract between buyers and auctioneer and the platform ownership have no statistically significant effects on the average decrease in procurement prices.Publication Open Access An empirical investigation of four well-known polynomial-size VRP formulations(NA, 2018) Öncan, Temel; Department of Business Administration; N/A; Aksen, Deniz; Sadatizamanabad, Mirehsan Hesam; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 40308; N/AThis study presents an in-depth computational analysis of four well-known Capacitated Vehicle Routing Problem (CVRP) formulations with polynomial number of subtour elimination constraints: a node-based formulation and three arc-based (single, two- and multi-commodity flow) formulations. For each formulation, several valid inequalities (VIs) are added for the purpose of tightening the formulation. Moreover, a simple topology-driven granulation scheme is proposed to reduce the number of a certain type of VIs. The lower and upper bounding performance and the solution efficiency of the formulations and respective VI configurations are benchmarked with state-of-the-art commercial optimization software. The extensive computational analysis embraces 121 instances with up to 100 customer nodes. We believe that our findings could be useful for practitioners as well as researchers developing algorithms for the CVRP.Publication Open Access An integrated analysis of capacity allocation and patient scheduling in presence of seasonal walk-ins(Springer, 2018) Çayırlı, Tuğba; Dursun, Pınar; Department of Business Administration; Güneş, Evrim Didem; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51391This study analyzes two decision levels in appointment system design in the context of clinics that face seasonal demand for scheduled and walk-in patients. The macro-level problem addresses access rules dealing with capacity allocation decisions in terms of how many slots to reserve for walk-ins and scheduled patients given fixed daily capacity for the clinic session. The micro-level problem addresses scheduling rules determining the specific time slots for scheduled arrivals. A fully-integrated simulation model is developed where daily demand actualized at the macro level becomes an input to the micro model that simulates the in-clinic dynamics, such as the arrivals of walk-ins and scheduled patients, as well as stochastic service times. The proposed integrated approach is shown to improve decision-making by considering patient lead times (i.e., indirect wait), direct wait times, and clinic overtime as relevant measures of performance. The traditional methods for evaluating appointment system performance are extended to incorporate multiple trade-offs. This allows combining both direct wait and indirect wait that are generally addressed separately due to time scale differences (minutes vs. days). The results confirm the benefits of addressing both decision levels in appointment system design simultaneously. We investigate how environmental factors affect the performance and the choice of appointment systems. The most critical environmental factors emerge as the demand load, seasonality level, and percentage of walk-ins, listed in the decreasing order of importance.Publication Open Access An investigation of time-inconsistency(Informs, 2009) Öncüler, Ayşe; Department of Business Administration; Department of Business Administration; Sayman, Serdar; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 112222Preference between two future outcomes may change over time-a phenomenon labeled as time inconsistency. The term "time inconsistency" is usually used to refer to cases in which a larger-later outcome is preferred over a smaller-sooner one when both are delayed by some time, but then with the passage of time a preference switches to the smaller-sooner outcome. The current paper presents four empirical studies showing that time inconsistency in the other direction is also possible: A person may prefer the smaller-sooner outcome when both options are in the future, but decide to wait for the larger-later one when the smaller option becomes immediately available. We. find that such "reverse time inconsistency" is more likely to be observed when the delays to and between the two outcomes are short (up to a week). We propose that reverse time inconsistency may be associated with a reversed-S shape discount function, and provide evidence that such a discount function captures part of the variation in intertemporal preferences.Publication Open Access Analysis of a general Markovian two-stage continuous-flow production system with a finite buffer(Elsevier, 2009) Gershwin, Stanley B.; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600Fluid flow models are used in the performance evaluation of production, computer, and telecommunication systems. In order to develop a methodology to analyze general Markovian continuous material flow production systems with two processing stages with an intermediate finite buffer, a general single-buffer fluid flow system is modelled as a continuous time, continuous-discrete state space stochastic process and the steady-state distribution is determined. Various performance measures such as the production rate and the expected buffer level are determined from the steady-state distributions. The flexibility of this methodology allows analysis of a wide range of models by specifying only the transition rates and the flow rates associated with the discrete states of each stage. Therefore, the method is proposed as a tool for performance evaluation of general Markovian continuous-flow systems with a finite buffer. The solution methodology is illustrated by analyzing a production system where each machine has multiple up and down states associated with their quality characteristics.Publication Open Access Analysis of a group purchasing organization under demand and price uncertainty(Springer, 2018) Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karabağ, Oktay; Faculty Member; Resercher; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; N/ABased on an industrial case study, we present a stochastic model of a supply chain consisting of a set of buyers and suppliers and a group purchasing organization (GPO). The GPO combines orders from buyers in a two-period model. Demand and price in the second period are random. An advance selling opportunity is available to all suppliers and buyers in the first-period market. Buyers decide how much to buy through the GPO in the first period and how much to procure from the market at a lower or higher price in the second period. Suppliers determine the amount of capacity to sell through the GPO in the first period and to hold in reserve in order to meet demand in the second period. The GPO conducts a uniform-price reverse auction to select suppliers and decides on the price that will be offered to buyers to maximize its profit. By determining the optimal decisions of buyers, suppliers, and the GPO, we answer the following questions: Do suppliers and buyers benefit from working with a GPO? How do the uncertainty in demand, the share of GPO orders in the advance sales market, and the uncertainty in price influence the players' decisions and profits? What are the characteristics of an environment that would encourage suppliers and buyers to work with a GPO? We show that a GPO helps buyers and suppliers to mitigate demand and price risks effectively while collecting a premium by serving as an intermediary between them.Publication Open Access Assortment-based cooperation between two make-to-stock firms(Taylor _ Francis, 2014) Department of Business Administration; Tan, Barış; Akçay, Yalçın; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 51400Cooperation can potentially improve competitiveness and profitability of firms with limited resources and production capacities. We present a continuous-time Markov chain model to study an assortment-based cooperation between two independent firms with limited capacity. An assortment-based cooperation is an agreement for combining the product assortments of the two firms and offering the combined assortment to each firm’s customers. We study both centralized and decentralized cooperations. In a centralized cooperation, firms jointly make replenishment decisions, whereas in the decentralized case, firms operate under independent base stock policies and manage product exchanges through a discount-based contract where each firm supplies its own product to the other firm at a discounted price and at an agreed fill rate. Under this scheme, assortment-based cooperation also mandates each firm to effectively ration their inventories since they have to deal with two different demand streams. The discount-based contract yields the results of the centralized operation by using specific values of the contract parameters. We also prove that assortment based cooperation is always beneficial for two symmetrical firms in both a centralized and a decentralized cooperation. Our numerical experiments reveal that assortment-based cooperation is not always beneficial if the firms are not symmetrical.Publication Open Access Automatic Interpretable Retail forecasting with promotional scenarios(Elsevier, 2020) Department of Business Administration; Ali, Özden Gür; Gürlek, Ragıp; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Business; 57780; N/ABudgeting and planning processes require medium-term sales forecasts with marketing scenarios. The complexity in modern retailing necessitates consistent, automatic forecasting and insight generation. Remedies to the high dimensionality problem have drawbacks; black box machine learning methods require voluminous data and lack insights, while regularization may bias causal estimates in interpretable models. The proposed FAIR (Fully Automatic Interpretable Retail forecasting) method supports the retail planning process with multi-step-ahead category-store level forecasts, scenario evaluations, and insights. It considers category-store specific seasonality, focaland cross-category marketing, and adaptive base sales while dealing with regularization-induced confounding. We show, with three chains from the IRI dataset involving 30 categories, that regularization-induced confounding decreases forecast accuracy. By including focal- and cross-category marketing, as well as random disturbances, forecast accuracy is increased. FAIR is more accurate than the black box machine learning method Boosted Trees and other benchmarks while also providing insights that are in line with the marketing literature.Publication Open Access Base-rate information in consumer attributions of product-harm crises(American Marketing Association (AMA), 2012) Lei, Jing; Dawar, Niraj; Department of Business Administration; Department of Business Administration; Canlı, Zeynep Gürhan; Researcher; Department of Business Administration; College of Administrative Sciences and Economics; 16135Consumers spontaneously construct attributions for negative events such as product-harm crises. Base-rate information influences these attributions. The research findings suggest that for brands with positive prior beliefs, a high (vs. low) base rate of product-harm crises leads to less blame if the crisis is said to be similar to others in the industry (referred to as the "discounting effect"). However, in the absence of similarity information, a low (vs. high) base rate of crises leads to less blame toward the brand (referred to as the "subtyping effect"). For brands with negative prior beliefs, the extent of blame attributed to the brand is unaffected by the base-rate and similarity information. Importantly, the same base-rate information may have a different effect on the attribution of a subsequent crisis depending on whether discounting or subtyping occurred in the attribution of the first crisis. Consumers who discount a first crisis also tend to discount a second crisis for the same brand, whereas consumers who subtype a first crisis are unlikely to subtype again.Publication Open Access Behavioral functioning of school-aged children with non-syndromic craniosynostosis(Springer, 2020) Zeytinoğlu Saydam, Senem; Özek, M. Memet; Crerand, Canice; Department of Business Administration; Marcus, Justin; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 124653Purpose: this study investigated the risk for children with non-syndromic craniosynostosis to develop behavioral problems during school age determined by the type of craniosynostisis, age at first surgery, and number of surgeries. Method: final sample consisted of 43 children aged between 6 years and 8 months and 17 years and 1 month (M = 10 years and 5 months). Behavioral problems were assessed with Child Behavioral Checklist (CBCL). Results: our sample had higher scores on the CBCL than the general population; specific elevations were observed including somatic complaints, aggressive behavior, social problems, attention problems, and thought problems and rule-breaking behavior. Behavioral functioning varied by number of surgical procedures, type of craniosynostosis, and age at first surgery. Conclusion: for school-aged NSC children's behavioral functioning, diagnosis specific patterns especially impacted by the first age of the surgery and number of surgeries.