Research Outputs

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A bicriteria approach to the two-machine flow shop scheduling problem
(Elsevier Science Bv, 1999) N/A; Department of Business Administration; Department of Business Administration; Sayın, Serpil; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; College of Administrative Sciences and Economics; 6755; 38819
In this paper we address the problem of minimizing makespan and sum of completion times simultaneously in a two-machine flow shop environment. We formulate the problem as a bicriteria scheduling problem, and develop a branch-and-bound procedure that iteratively solves restricted single objective scheduling problems until the set of efficient solutions is completely enumerated. We report computational results, and explore certain properties of the set of efficient solutions. We then discuss their implications for the Decision Maker.
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A bilevel fixed charge location model for facilities under imminent attack
(Pergamon-Elsevier Science Ltd, 2012) Aras, Necati; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308
We investigate a bilevel fixed charge facility location problem for a system planner (the defender) who has to provide public service to customers. The defender cannot dictate customer-facility assignments since the customers pick their facility of choice according to its proximity. Thus, each facility must have sufficient capacity installed to accommodate all customers for whom it is the closest one. Facilities can be opened either in the protected or unprotected mode. Protection immunizes against an attacker who is capable of destroying at most r unprotected facilities in the worst-case scenario. Partial protection or interdiction is not possible. The defender selects facility sites from m candidate locations which have different costs. The attacker is assumed to know the unprotected facilities with certainty. He makes his interdiction plan so as to maximize the total post-attack cost incurred by the defender. If a facility has been interdicted, its customers are reallocated to the closest available facilities making capacity expansion necessary. The problem is formulated as a static Stackelberg game between the defender (leader) and the attacker (follower). Two solution methods are proposed. The first is a tabu search heuristic where a hash function calculates and records the hash values of all visited solutions for the purpose of avoiding cycling. The second is a sequential method in which the location and protection decisions are separated. Both methods are tested on 60 randomly generated instances in which m ranges from 10 to 30, and r varies between 1 and 3. The solutions are further validated by means of an exhaustive search algorithm. Test results show that the defender's facility opening plan is sensitive to the protection and distance costs.
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A Bilevel p-median model for the planning and protection of critical facilities
(Springer, 2013) Aras, Necati; Piyade, Nuray; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308
The bilevel p-median problem for the planning and protection of critical facilities involves a static Stackelberg game between a system planner (defender) and a potential attacker. The system planner determines firstly where to open p critical service facilities, and secondly which of them to protect with a limited protection budget. Following this twofold action, the attacker decides which facilities to interdict simultaneously, where the maximum number of interdictions is fixed. Partial protection or interdiction of a facility is not possible. Both the defender's and the attacker's actions have deterministic outcome; i.e., once protected, a facility becomes completely immune to interdiction, and an attack on an unprotected facility destroys it beyond repair. Moreover, the attacker has perfect information about the location and protection status of facilities; hence he would never attack a protected facility. We formulate a bilevel integer program (BIP) for this problem, in which the defender takes on the leader's role and the attacker acts as the follower. We propose and compare three different methods to solve the BIP. The first method is an optimal exhaustive search algorithm with exponential time complexity. The second one is a two-phase tabu search heuristic developed to overcome the first method's impracticality on large-sized problem instances. Finally, the third one is a sequential solution method in which the defender's location and protection decisions are separated. The efficiency of these three methods is extensively tested on 75 randomly generated instances each with two budget levels. The results show that protection budget plays a significant role in maintaining the service accessibility of critical facilities in the worst-case interdiction scenario.
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A bilevel partial interdiction problem with capacitated facilities and demand outsourcing
(Elsevier, 2014) Akça, Sema Şengul; Aras, Necati; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308
In this paper, partial facility interdiction decisions are integrated for the first time into a median type network interdiction problem with capacitated facilities and outsourcing option. The problem is modeled as a static Stackelberg game between an intelligent attacker and a defender. The attacker's (leader's) objective is to cause the maximum (worst-case) disruption in an existing service network subject to an interdiction budget. On the other hand, the defender (follower) is responsible for satisfying the demand of all customers while minimizing the total demand-weighted transportation and outsourcing cost in the wake of the worst-case attack. She should consider the capacity reduction at the interdicted facilities where the number of interdictions cannot be known a priori, but depends on the attacker's budget allocation. We propose two different methods to solve this bilevel programming problem. The first one is a progressive grid search which is not viable on large sized instances. The second one is a multi-start simplex search heuristic developed to overcome the exponential time complexity of the first method. We also use an exhaustive search method to solve all combinations of full interdiction to assess the advantage of partial interdiction for the attacker. The test results suggest that under the partial interdiction approach the attacker can achieve a better utilization of his limited resources.
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A bourdieuan relational perspective for entrepreneurship research
(Wiley, 2014) Tatli, Ahu; Vassilopoulou, Joana; Forson, Cynthia; Slutskaya, Natasha; Department of Business Administration; Özbilgin, Mustafa; Other; Department of Business Administration; College of Administrative Sciences and Economics; N/A
In this paper, we illustrate the possibilities a relational perspective offers for overcoming the dominant dichotomies (e.g., qualitative versus quantitative, agency versus structure) that exist in the study of entrepreneurial phenomena. Relational perspective is an approach to research that allows the exploration of a phenomenon, such as entrepreneurship, as irreducibly interconnected sets of relationships. We demonstrate how Pierre Bourdieu's concepts may be mobilized to offer an exemplary toolkit for a relational perspective in entrepreneurship research.
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A construal level account of the impact of religion and god on prosociality
(Sage, 2020) N/A; N/A; Department of Business Administration; Canlı, Zeynep Gürhan; Karataş, Mustafa; PhD Student; Faculty Member; Department of Business Administration; Graduate School of Business; College of Administrative Sciences and Economics; N/A; 16135
This research shows that the two most prevalent religious constructs-God and religion-differentially impact cognition. Activating thoughts about God (vs. religion) induces a relatively more abstract (vs. concrete) mindset (Studies 1a-1c). Consequently, time donation intentions (Study 2) and actual monetary donations (Study 3) after a God (vs. religion) prime increase when people are presented an abstractly (vs. concretely) framed donation appeal. Similarly, people donate more money to distant (vs. close) donation targets, which are construed relatively abstractly (vs. concretely), when a religious speech activates predominantly God-specific (vs. religion-specific) thoughts (Study 4). These effects are mediated by "feeling right" under construal level fit (Study 3). Overall, this research significantly advances extant knowledge on religious cognition and past research on the link between religion and prosociality.
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A decision support framework for evaluating revenue performance in sequential purchase contexts
(Elsevier Science Bv, 2017) Öztürk, O. Cem; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819
This paper studies the product ordering problem in sequential purchase contexts where sellers aim to maximize their revenue faced with budget constrained buyers. We propose a multi-layered decision support framework that combines empirical data with simulation, optimization, and econometric methods to address this problem. Our framework allows sellers to: (i) compare revenue performances of limited information sequencing strategies, (ii) quantify benchmark revenue levels that can be achieved via the optimal sequence based on detailed buyer information, (iii) determine the costs of limited information and strategic buyers to the seller, and (iv) identify the moderators of sequencing strategy performance. We illustrate our framework through two applications in a business-to-business used-car auction setting. Contrary to previous studies reporting practitioners’ tendency to sequence items from the lowest value to the highest, our results suggest that the best-performing limited information sequencing strategy depends on buyers’ bidding behavior. We also find that the revenue difference between the optimal sequence and a limited information sequencing strategy can be substantial. Our results show that a significant portion of this revenue difference is associated with the seller’s limited information on buyers’ budgets and product valuations. Our applications also provide various sensitivity analyses and develop new propositions on the moderators of the relationship between the seller’s revenue and sequencing strategies.
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A decomposition model for continuous materials flow production systems
(Taylor & Francis, 1997) Yeralan, Sencer; Department of Business Administration; N/A; Tan, Barış; Faculty Member; N/A; Department of Business Administration; College of Administrative Sciences and Economics; N/A; 28600; N/A
This study presents a general and flexible decomposition method for continuous materials flow production systems. The decomposition method uses the station model developed in the first part of this study (Yeralan and Tan 1997). The decomposition method is an iterative method. At each iteration the input and output processes of the station model are matched to the most recent solutions of the adjacent stations. The procedure terminates when the solutions converge and the conservation of materials flow is satisfied. The decomposition method does not alter the station parameters such as the breakdown, repair, and service rates. This method can be used to analyse a wide variety of production systems built from heterogeneous stations. The properties of the decomposition method are studied for the series arrangement of workstations. The convergence and uniqueness of the decomposition method are discussed. The method is compared to other approximation methods. The complexity of the decomposition method is empirically investigated and is shown to be in the order of N-2 where N is the number of stations in the line, irrespective of the buffer capacities.
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A dynamic analysis of market entry rates in a global industry: a community ecology perspective
(Emerald, 1999) Çavuşgil, S. Tamer; Department of Business Administration; Tunalı, Ayşegül Özsomer; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 108158
States that it is critical that incumbent firms understand the processes that enhance or inhibit entry of new firms into their industry. A new entrant into an industry may create additional demand by legitimizing the technology/products, and/or may share the existing market by drawing buyers away from incumbents. An analysis of market entry rates is especially important in new, high technology industries where sub‐groups of firms pursue different technology and global market diversification strategies because such sub‐groups may have asymmetrical cross‐effects on entry rates of new firms. Suggests a community ecology approach to assessing the impact of industry density on new firm entry rates. The framework is demonstrated by applying it to the global personal computer industry during the period of 1977‐1992. Results suggest that density has a nonmonotonic positive effect, while the firm‐level variables of technological strategy and market expansion strategies have a monotonic positive effect on new firm entry rates.
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A fuzzy decomposition method for multistation production systems subject to blocking
(Elsevier Science Bv, 1996) Yeralan, Sencer; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600
This study presents a new methodology to adjust the value of the proportionality constant (step length parameter) used in the general decomposition method for multistation heterogeneous production systems proposed in an earlier study for specially unbalanced production systems by using fuzzy logic control. The decomposition method is based on successive approximations. Namely, input rate to each subsystem is adjusted proportional to the difference in production rates of adjacent stations. This process continues until all the subsystems have the same production rate, Fuzzy logic control uses basic observations described in linguistic variables of how production rate changes as a function of input rate, Consequently, the proportionality constant in the successive approximation method is adjusted. These observations are not model specific, Thus, the fuzzy decomposition method can be applied to a wide variety of production systems. The same methodology can also be used in other applications where adjusting the step length parameter to attain the highest convergence rate is not trivial. For example, step length parameter used in subgradient optimization and other search methodologies can also be adjusted by using the fuzzy logic control methodology presented in this study. Numerical experience shows that this method yields a substantial improvement in the convergence rate of the decomposition method for highly unbalanced production system.
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A game theoretic model and empirical analysis of spammer strategies
(Conference on Email and Anti-Spam, CEAS, 2010) Parameswaran, Manoj; Rui, Huaxia; Whinston, Andrew B.; Department of Business Administration; Sayın, Serpil; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 6755
Network security problems are deteriorating worldwide, and can potentially undermine the growth of the digital economy and imperil the multitude of innovations that have been a significant driver of economic growth as well as providing increased services to individuals, businesses, and governments. The emergence of botnets as a powerful force undermining security has raised new and important issues. In particular, the difficulty of detection, elimination and prevention of botnets or spam caused thereof on an absolute scale using computing technologies alone have focused attention on studying behavior patterns of botnets and spammers, to help devise better countermeasures. This paper has two objectives; first to introduce a theoretical modeling approach to spammer behavior and derivation of the model, and second, to compare some of the derivations with data that has been collected from blocklist organizations. By making inferences about the blocklist rules, the spammer can strategize to maximize the amount of spam sent, and we find evidence of spammers using multiple strategies. The blocklist can achieve reduction of spam by investigating longer history of a node's behavior instead of focusing on detection alone. While some of the derivations seem consistent with the data there is considerable room for modification and extension of the modeling approach. The paper concludes with suggestion for the extension of the model.
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A global brand management roadmap
(Elsevier, 2012) Batra, Rajeev; Chattopadhyay, Amitava; ter Hofstede, Frenkel; Department of Business Administration; Tunalı, Ayşegül Özsomer; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 108158
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A lab-scale manufacturing system environment to investigate data-driven production control approaches
(Elsevier Sci Ltd, 2021) N/A; N/A; Department of Business Administration; Khayyati, Siamak; Tan, Barış; PhD Student; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; N/A; 28600
Controlling production and release of material into a manufacturing system effectively can lower work-inprogress inventory and cycle time while ensuring the desired throughput. With the extensive data collected from manufacturing systems, developing an effective real-time control policy helps achieving this goal. Validating new control methods using the real manufacturing systems may not be possible before implementation. Similarly, using simulation models can result in overlooking critical aspects of the performance of a new control method. In order to overcome these shortcomings, using a lab-scale physical model of a given manufacturing system can be beneficial. We discuss the construction and the usage of a lab-scale physical model to investigate the implementation of a data-driven production control policy in a production/inventory system. As a datadriven production control policy, the marking-dependent threshold policy is used. This policy leverages the partial information gathered from the demand and production processes by using joint simulation and optimization to determine the optimal thresholds. We illustrate the construction of the lab-scale model by using LEGO Technic parts and controlling the model with the marking-dependent policy with the data collected from the system. By collecting data directly from the lab-scale production/inventory system, we show how and why the analytical modeling of the system can be erroneous in predicting the dynamics of the system and how it can be improved. These errors affect optimization of the system using these models adversely. In comparison, the datadriven method presented in this study is considerably less prone to be affected by the differences between the physical system and its analytical representation. These experiments show that using a lab-scale manufacturing system environment is very useful to investigate different data-driven control policies before their implementation and the marking-dependent threshold policy is an effective data-driven policy to optimize material flow in manufacturing systems.
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A location-routing problem for the conversion to the "click-and-mortar" retailing: the static case
(Elsevier, 2008) Altınkemer, Kemal; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308
The static conversion from brick-and-mortar retailing to the hybrid click-and-mortar business model is studied from the perspective of distribution logistics. Retailers run warehouses and brick-and-mortar stores to meet the demand of their walk-in customers. When they decide to operate on the Web as an e-tailer, also click-and-mortar stores are needed which can serve both walk-in and online customers. While the distance between home and the nearest open store is used as a proxy measure for walk-in customers, a quality of service (QoS) guarantee for online customers is timely delivery of their orders. We describe and solve a static location-routing based problem for companies that embrace the clicks-and-bricks strategy in their retail operations. An augmented Lagrangian relaxation method embedded in a subgradient optimization procedure generates lower bounds, whereas a heuristic method finds feasible solutions. The performance of the Lagrangian-based solution method is tested on a number of randomly generated test problems.
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 Economics
Customer 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.
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 Economics
Managers 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.
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A longitudinal examination of the asymmetric impact of employee and customer satisfaction on retail sales
(Emerald Group Publishing, 2006) Keiningham, T.L.; Cooil, B.; Peterson, K.; Vavra, T.G.; Department of Business Administration; Aksoy, Lerzan; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; N/A
Purpose The purpose of this research is to examine changes in, and consistency of customer and employee satisfaction for asymmetry with regard to sales changes for a large US specialty goods retailer. Design-methodology-approach The data came from a 125 store US specialty goods retailer. Customer and employee data represent surveys administered by the firm in 2000 and 2001. Over 34,000 customer questionnaires and 3,900+ employee questionnaires were collected for the study. Pearson correlations and CHAID analyses were used to test the hypotheses. Findings For satisfaction employee and customer to impact changes in sales, perceived performance standards on some dimensions must be consistently delivered and changes in satisfaction levels must cross attribute-specific threshold levels. Research limitations-implications As the data comes from a single retailer, it is not possible to conclusively generalize these findings to all other retailers, or to other industries. Practical implications For managers, the typical reliance on simple mean employee or customer satisfaction scores or indexes is unlikely to adequately explain changes in sales. Managers must achieve satisfaction levels on those attributes where consistent performance is linked to sales. Additionally, given the threshold nature of the relationship, it is critical that managers be certain that efforts designed to improve satisfaction do so in sufficient force so as to reach levels that correspond with increasing sales. Originality-value While the literature has shown asymmetry in the relationship between customer satisfaction and customer behavior, to date no research has examined possible asymmetry in employee satisfaction data and business performance. Furthermore, analyses of asymmetry in customer satisfaction data have largely focused on cross-sectional data and individual-level customer data as opposed to business performance indicators. Understanding the asymmetric nature of the examined relationships should result in better allocation and use of marketing resources.
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/A
Given 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.
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A matheuristic for leader-follower games involving facility location-protection-interdiction decisions
(Springer, 2013) Aras, Necati; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308
The topic of this chapter is the application of a matheuristic to the leaderfollower type of games-also called static Stackelberg games-that occur in the context of discrete location theory. The players of the game are a system planner (the leader) and an attacker (the follower). The decisions of the former are related to locating/relocating facilities as well as protecting some of those to provide service. The attacker, on the other hand, is interested in destroying (interdicting) facilities to cause the maximal possible disruption in service provision or accessibility. The motivation in the presented models is to identify the facilities that are most likely to be targeted by the attacker, and to devise a protection plan to minimize the resulting disruption on coverage as well as median type supply/demand or service networks. Stackelberg games can be formulated as a bilevel programming problem where the upper and the lower level problems with conflicting objectives belong to the leader and the follower, respectively. In this chapter, we first discuss the state of the art of the existing literature on both facility and network interdiction problems. Secondly, we present two fixed-charge facility location-protection-interdiction models applicable to coverage and median-type service network design problems. Out of these two, we focus on the latter model which also involves initial capacity planning and post-attack capacity expansion decisions on behalf of the leader. For this bilevel model, we develop a matheuristic which searches the solution space of the upper level problem according to tabu search principles, and resorts to a CPLEXbased exact solution technique to tackle the lower level problem. In addition, we also demonstrate the computational efficiency of using a hash function, which helps to uniquely identify and record all the solutions visited, thereby avoids cycling altogether throughout the tabu search iterations
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; 38819
Empirical 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.