Graduate School of Business

Permanent URI for this collectionhttps://hdl.handle.net/10679/9880

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Consumer studies about purchase, repeat purchase and word-of-mouth after deep discount online
(2015-06) Arı, Ela; Pauwels, Koen; Pauwels, Koen; Börü, D.; Doğan, Kutsal; Atakan, Şükriye Sinem; İyigün, N. Ö.; Department of Business; Arı, Ela
Daily deal sites are e-commerce businesses that offer deep discounts (e.g., 50%, 90%) for products and services to consumers through local service providers. These sites increase consumer's buying power and attract more customers for local service providers. The fact that most deal sites keep half of the revenue from each consumer makes this model unprofitable for service providers. To increase the viability of this business model, after purchasing from deal sites, consumers would need to repurchase at full and/or different discount rates from service providers and generate positive Word of Mouth (WOM). For that aim, three studies were conducted. The first study is a survey conducted in Turkey, which examines the consumer motivations based on McClelland Need Theory. The results revealed that need for achievement affects deal purchases while need for group affiliation drives the intention to repurchase at full price and need for power increases the generation of WOM. The second study addresses consumer motivations through a multi-method approach, combining in-depth interviews with an experimental study. The results revealed that price discount and distance are key action variables that managers can control in order to give fewer discounts and make higher profits. Moreover, consumers with a high need for achievement are more likely to generate WOM, while those with a high need for affiliation create more electronic WOM (eWOM). The third study is an experimental study, which reveals that satisfaction is a primary driver for repurchase and WOM. Furthermore, consumer characteristics as coupon proneness and price quality schema are key characteristics for both deal sites and service providers.
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Corporate sustainability interactions and corporate financial performance
(2017-11) Uşar, Damla Durak; Denizel, Meltem; Soytaş, Mehmet Ali; Denizel, Meltem; Ekici, Özgün; Özen, Ulaş; Akkan, C.; Sayın, S.; Department of Business; Uşar, Damla Durak
There is a large amount of empirical literature focused on the relationship between corporate sustainability and corporate financial performance. The literature considers firm specific aspects affecting the link but omits the influence of the competition. I view the sustainability decisions of companies as strategic decisions and use the Stackelberg game to model the effect of competition and sustainability spillovers on sustainability interactions. I rely on computational methods to identify the conditions, when the first mover advantage or the second mover advantage arises. I turn to empirical methods in order to validate the inferences made from the analytical model and estimate the parameters of the discrete choice model using the social performance ratings from MSCI KLD 400 Social Index and financial information from Wharton Research Data Services' COMPUSTAT dataset. Although the interdependence of discrete entry decisions can pose identification and estimation problems, I provide empirical evidence that the effect of competition on the likelihood of entry into the sustainability market dominates the effect of spillover. Furthermore, this finding is more profound for first time entrants.
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Digital maturity measurement based on the stages of digital business transformation a study in the automotive sales and aftersales sector
Mutlu, Irmak; Hartigh, Erik Den; Hartigh, Erik Den; Üçler, Çağlar; Fiş, Ahmet Murat; Zeytinoğlu, G. N.; Tunçalp, D.; Department of Business; Mutlu, Irmak
Digital transformation is the change of socio-economic structures such as business models, supply chains, platforms, or ecosystems as a consequence of the use of digital technology. Consistent with the previous research on understanding digital transformation, the transformational change of organizations, business models, platforms or ecosystems are triggered by digital technology exposure. Therefore, the impact of digital technologies on the digital transformation of companies and internal organizational aspects plays a critical role in literature as well as industrial practice. This transformational change triggered by the technologies raised the question about the digital maturity measurement or readiness assessment. The digital maturity model proposed in this study brings a new approach to both academics and practitioners in digital transformation literature regarding the digital measurement of the companies. This research mainly aims to answer, “How can the digital maturity level of an organization be measured?”. Research of the digital maturity measurement of organizations structured according to the following four parts: (1) Stages of Digital Business Transformation, (2) Organizational Aspects of Digital Maturity, (3) Digital Maturity Index (DMI) Development, and (4) Digital Maturity Index for Measurement. The chapters of the research are structured based on Churchill’s 8 steps for and Digital Maturity Index (DMI) Development and Implementation eight steps [1]. The findings for the four parts are (1) The stages of digital business transformation, (2) Organizational aspects of digital maturity, (3) Digital Maturity Index (DMI) as an instrument, (4) Digital Maturity Index (DMI) implementation findings. The first part focuses on defining and differentiating among core concepts of digital business transformation, i.e., digitization, digitalization, and digital transformation and stages’ arrangement from digitization to digital transformation. In this part, 5 stages are derived from expert interviews and literature reviews as the progressive stages of digital business transformation. At the end of this part, (i) digital passive, (ii) digitization, (iii) digitalization, (iv) digital transition, and (v) digital transformation have been identified as the digital business transformation stages. The second part focuses on identification of the digital technology types such as IoT Data, (The Internet of Things), Machine Learning and Artificial Intelligence (ML/AI), and the Cloud etc., all of which have a high impact on the digital transformation of the companies in automotive sales and aftersales sector as well as the extent digital technologies influence the organization’s internal digital transformation through components and structures so a company’s maturity stage progresses accordingly. Therefore, the scope focuses on what internal organizational aspects should be considered when measuring the digital transformation of the companies. These internal organizational aspects are derived from expert interviews and literature reviews such as Culture, Data and Analytics, People, Structure, and Organization, Processes and Systems, Strategy, and Technology. At the end of this part, these six aspects were identified as the internal organizational aspects. The third part focuses on the digital maturity stages and how to measure the digital maturity stage of an organization. Towards the identification of the stage of digital maturity, a digital maturity measurement tool named Digital Maturity Index (DMI) emerged. This part focuses on the Digital Maturity Index (DMI) design and development process covering the data collection and measure purification. In this part, all the findings of first and second parts are integrated as an input for the development of the DMI. The process steps cover literature review, expert interviews, and test phases. To investigate the main research questions (RQ), literature review, unstructured, and semi-structured interviews were conducted. The Digital Maturity Index (DMI) developed based on these literature and interview input as well as generated sample items. With the feedback and support of the PhD committee, and the business practitioner the measure is purified. The developed tool and its questions and rubrics were tested twice at the company with the participation of both the business departments and the IT departments. In total, two test workshops were organized and the feedback was gathered from the business and IT side as well as the feedback of the PhD committee. After integrating all the comments, the questionnaire became ready for the roll out. At the end of this part, as a digital maturity measurement tool an index was developed. The fourth part focuses on validity and reliability assessment of the developed digital maturity model and its business practice empirical implementation after the development of the Digital Maturity Index (DMI) as an instrument. Statistical findings from the empirically tested model are developed. It was complemented with the qualitative interview. This model both theoretically and empirically confirms the proposed hypothetical model’s validation. The DMI was introduced to the management. Then, as the next step two workshops were organized to collaboratively define the digital maturity stage of the company. The workshop participants were grouped into four categories: Managers, IT Expert, Business Expert and Beneficiaries. The questionnaire was rolled out and data analysis was completed using SPSS as a tool. Furthermore, the results of DMI analysis were presented to the upper management and presented to the participants in a workshop format. Any feedback coming out of these meetings was integrated into the analysis. As the final step to validate the findings, a 2nd round of interviews was conducted with several experts who also contributed to the DMI implementation phase. Finally, the statistical analysis was completed, and the results integrated, and questions not supported qualitatively and quantitively not supported questions eliminated and DMI questions were reduced to 31. Finally, at the end of this part, Digital Maturity Index (DMI) as a measurement instrument developed as a norm. The Digital Maturity Index (DMI) development and implementation process is synchronized with the steps of Churchill’s “Procedure for Developing Better Measures” [1]. In parallel to the Churchill procedure, the Digital Maturity Index (DMI) Development and Implementation steps in this research is grouped under eight steps: (1) Literature review and 1st Round of interview findings, (2) DMI development and individual feedback sessions, (3) Test phase 1, (4) Test phase 2, (5) DMI implementation, (6) DMI results and qualitative and quantitative analysis, (7) 2nd round of interview findings and improvement areas, and (8) Finalize DMI instrument. In parallel to DMI Development and Implementation steps, based on Churchill’s procedure, the measure development process follows eight steps: (1) Specify the domain of the construct, (2) General sample of items, (3) Collect data, (4) Purify measure, (5) Collect data, (6) Assess reliability, (7) Assess validity, (8) Develop norm [1]. This research contributes to the literature by delivering a digital maturity measurement model which merges the academic and practitioner contributions and brings a new insight into organization’s digital maturity measurement literature. The developed model was tested at an automotive company, but it was developed considering cross industry implementation.
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Essays in macro-finance
(2019-12-26) Usta, Ahmet; Özlale, Ümit; Güntay, Levent; Ekici, Özgün; Hasanov, M.; Eroğlu, B. A.; Özlale, Ümit; Department of Business; Usta, Ahmet
This dissertation includes three essays within macro-finance literature ranging from international macroeconomics, to labor and housing market dynamics. While the focus of first essay is more on international, particular focus of last two essays is on the Turkish economy. In the first essay, we examine the impacts of unconventional monetary policies, stock market volatilities, and banking conditions in center economies including the US, UK, and Europe on macroeconomic and financial performance of a sample of emerging economies, which consists of Brazil, Russia, India, China, South Africa, Turkey, and Indonesia over the period between 2009:M1 and 2017:M12. Using dynamic factor modelling approach, we find significant roles of asset purchase program by the Fed, volatility conditions in the UK, and European banking conditions in shaping the global financial and economic conditions. Second essay investigates the role of sentiment, which is aggregate investor attitude, in explaining asset prices within housing market framework. We uncover the long run relationship among sentiment, housing credit and prices, and supply in Turkish housing market over the period between 2010:M1 and 2018:M6. We find that the sentiment is significant in forecasting housing credit and supply in the short run. The sentiment is also a significant factor at work in explaining the housing prices and supply of dwellings in the long run. The third essay is at the intersection of corporate finance and labor market. We examine the effect of going public on employment level in firms. Moreover, we investigate the main motivation behind issuing equity by considering the use of capital raised at initial public offerings (IPO) date. To do so, we consider IPO listed firms in Borsa Istanbul (BIST) and use annual data from financial reports between 2000 and 2016. We find that accessing public equity market has positive impact on employment growth through accessing debt market. As their borrowing abilities improve, firms tend to increase their expenditures on physical capital. In turn, firms need to hire more employees to run their operations. When compared to mature firms, young firms have higher employment growth. Moreover, we find that the labor productivity is higher for large firms.
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Essays on pricing anomalies and the limits of arbitrage in emerging markets
(2016-07) Şatıroğlu, Sait; Şener, Emrah; Akgiray, Ahmet Vedat; Department of Business; Şatıroğlu, Sait
It is a difficult task to explain market anomalies in standard models of asset pricing, as they are all based on the core idea of the law of one price: two assets with equal expected returns have equal values. Otherwise, there is an arbitrage opportunity. However, arbitrage opportunities should not last for an extended period, as arbitrageurs should eventually locate the apparent mispricing, provide liquidity to markets, and keep prices in line with the asset's fundamentals. The Lehman crisis gives an opportunity to investigate both the behavioral and economic causes of deviations from the law of one price parity. Therefore, this dissertation thesis is focused on the empirical analysis of deviations from the law of one price parity using covered interest rate parity (CIRP) metric. It consists of three parts; the first two parts deal with the analysis of CIRP from different angles. The third part focused on finding an answer to the question, whether a market-based indicator created by the country-specific risk factors of CIRP deviations would be a major sign that can produce early warnings for the Turkish market. In the first chapter, I use the covered interest rate parity metric to measure violations of the law of one price parity (LOP) for currencies of developed and emerging economies. Across the five maturity point, I investigate both the time-series and cross-sectional variation of this LOP metric which severely violated during periods of financial distress. Dynamic factor analysis reveals that LOP deviations are time varying and state dependent for both markets and driven by two factors, namely: Global and Local factors. I construct empirical proxies for these factors and run a comprehensive investigation about economic drivers of this anomaly in three separate phases, pre-crisis, crisis (liquidity and credit crisis) and post crisis. My findings show that CIRP deviations on the global risk component and the country-specific risk components show distinct dynamics across developed and emerging countries. During the first phase of the crises, the global funding and liquidity factors are significant and shared to both markets, however, after the Lehman collapse while sentiment factors have a considerable impact on developed markets, the country-specific risk factors turn to be the main factors for emerging markets. In addition, financial contagion in developed markets, in terms of one way price discovery and volatility spillover does not appear to be valid for emerging markets CIRP deviations. Therefore, in the return and volatility levels, contagion in emerging countries indicate different local characteristics. The collapse of the recent housing price bubble brought the global economy to its knees and caused international funding liquidity to dry up. In the second chapter, I investigate how economic policies during the crisis impacted global liquidity by examining the covered interest rate parity condition. I find that swap lines orchestrated by the Federal Reserve, stress test announcements, and other governmental policies and news events had a significant impact on CIRP violations. My findings indicate that policies pursued during the crisis helped relieve market frictions in foreign exchange markets and that the result of these policies differed for developed and emerging markets. Most economists would argue that the seeds of the financial crisis were planted some time before the onset of the crisis. Hence, in the third chapter, I investigate whether the country-specific risk factors of CIRP deviations can be used as an early warning indicator for a local economy, namely Turkey, and create a blended index, so that regulators can be increasingly forward-looking hence pre-emptive rather than reactive in the century of high-speed information flow.
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The impact of brand architecture decisions on portfolio sales
(2017-06) Sezen, Burcu; Pauwels, Koen Hendrik; Pauwels, Koen Hendrik; Ataman, M. B.; Tunalı, A. Ö.; Akşit, Mina Seraj; Canlı, Z. G.; Department of Business; Sezen, Burcu
Decisions pertaining to the organization of products under brands within the company's portfolio are an important aspect of brand portfolio strategy with potentially serious top-and bottom-line implications. Despite the critical role brand architecture decisions play on profitability, there is little empirical evidence on how the strength of the link established among clusters of products within the company's portfolio impacts company performance. To advance our understanding in this domain, this paper scrutinizes the effect of different brand architecture strategies (master brand with sub-brands vs stand-alone brand strategy) in moderating the impact of marketing actions (price promotion and new product introduction) on total portfolio sales. Using insights from diagnosticity-accessibility theory, the authors develop hypotheses as to whether and when a certain marketing action is expected to generate greater portfolio sales and how the differentiation level of products within the portfolio may interfere. The hypotheses are tested by means of a sales decomposition model, which traces demand redistribution in response to a focal brand's marketing actions among linked (master brand with sub-brands), unlinked (stand-alone), and other brands in the category. In the empirical application, the authors use the coffee category in the IRI Academic Data Set. The results have the managerial implication that companies that use predominantly stand-alone brands benefit from price promotions more than subbrands. The reverse implication is true for line extensions.
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Institutional herding in Borsa İstanbul
Kıygı, Okay; Yalçın, Atakan; Yalçın, Atakan; Güntay, Levent; Özsoy, Satı Mehmet; Atılgan, Y.; Ercan, M.; Department of Business
Herding is defined as a group of investors imitating the actions of other investors instead of following their own beliefs and information. It is argued that institutional investors have several reasons to herd. The theoretical explanations of herding are categorized as informational cascades, reputational and compensational herding, characteristic herding, investigative herding and fads. The herding behaviour of both domestic and foreign institutional investors is analysed in Borsa İstanbul between March 2006 and September 2018 by using the Sias [1]’s herding measure. The institutional demand for stocks in the current quarter is positively correlated with the institutional demand for stocks in the previous quarter for both domestic and foreign institutional investors. This positive relation is decomposed into institutional investors following their own lag trades and institutional investors following each other into and out of the same securities (''herding'') parts. This positive relation is not caused by the characteristics herding and momentum trading strategies. The institutional demand for stocks in the current quarter has no destabilizing effect on future stock returns. The domestic institutional investors herd only in small-capitalization stocks which is interpreted as informational cascades. The foreign institutional investors herd in both small and large-capitalization stocks. The evidence of herding in large capitalization stocks is interpreted as investigative herding. The domestic institutions implement negative feedback trading strategies in large-capitalization stocks while foreign institutional investors implement positive feedback trading strategies in large capitalization stocks
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Liquidity in the emerging market local currency bond market: measurement,commonality, and supply of risk capital
(2016-06) Baronyan, Sayad Reteos; Şener, Emrah; Akgiray, Ahmet Vedat; Department of Business; Baronyan, Sayad Reteos
Major emerging markets sovereigns have started financing a significant component of their budget deficits issuing local currency (LC) bond, reaching to the total outstanding size over 5 trillion dollar almost half of the size of the US Treasury markets. The current consensus is that LC bond yields are rather rich with respect to benchmark U.S. Treasury rates and the literature argues that this occurs as a compensation two major types of risk: currency (depreciation) risk and credit (default) risk. I contribute to this literature by investigating the role of liquidity risk in these markets. Moreover, we investigate if liquidity risk is specific to the characteristics of the issuing country (thus diversifiable) or rather affected by global effects related to global asset markets (thus un-diversifiable). To address these questions, I build a unique bond-specific data set covering major LC markets until November 2015. I study the role of several liquidity measures in the context of LC bonds to identify potentially different channels of liquidity shock transmission. I find strong evidence that LC bond liquidity i) is a priced-factor, (ii) is state-dependent, and (iii) shows significant commonality across countries. I also document the new evidence that procylical nature of global LC bond funds domiciled in developed countries can destabilize LC bond market liquidity with potential adverse consequences for the LC debt markets. As liquidity provision is an important function in general and crucial in periods of market stress, EM economies that are relying heavily on pro-cyclical investors such as global bond mutual funds should comprehend, how activities of asset managers and their investor base can affect EM economies.
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Macroeconomic fundamentals and emerging market asset prices
(2017-06) Yılmaz, Osman; Şener, Emrah; Akgiray, Ahmet Vedat; Şener, Emrah; Akgiray, Ahmet Vedat; Department of Business; Yılmaz, Osman
This thesis consists of three chapters which make empirical contributions to the field of emerging markets xed income, real estate and nancial markets. First chapter entitled 'Macroeconomics Fundamentals and Emerging Market Local Currency Debt'focus on Emerging market (EM) local currency debt market which is largely absent from the academic literature, despite the increasingly important role of local currency debt for EM sovereign issuers and its increasing share in the portfolio of foreign investors. In this chapter, I investigate the effects of macroeconomic fundamentals on EM local currency bond markets using a dynamic factor approach based on a large panel of economic and financial time series. I find strong predictable variation in the EM local currency excess bond returns that is associated with macroeconomic activity. I provide evidence that the main predictor variables are the factors based on real economic activity that are highly correlated with measures of industrial and manufacturing production, but factors based on global financial factors also contain information about the future local currency bond returns. The predictive power of the extracted factors is not just statistically significant but also economically important. In the second chapter entitled 'Predictability of Emerging Market Real Estate Prices' I approximate large information set of EM real estate market by large panel of economic and financial time series used in the first chapter. One of the main contributions of this chapter to the empirical literature is to document the mutuality of top three factors predicting the real house price fluctuations in a sample of leading emerging economies including Brazil, Mexico, South Africa, and Turkey. As two-thirds of the almost 50 systemic banking crises in recent decades were preceded by boom-bust patterns in house prices, I believe that my findings have important implications for policymakers and pension fund managers. Finally, third chapter entitled 'Forecasting Turkish Real GDP Using Targeted Predictors' examines whether there is any merit of selecting a limited number of variables for superior forecasting performance. A number of recent studies in current literature discuss the usefulness of factor models in the context of GDP forecasting using large panels of macroeconomic variables. However, there is no consensus on how to identify informative variables from a large set of relevant indicators for the purpose of GDP prediction. Including too many variables in the analysis is likely to cause complications in extracting appropriate signal for the factor model framework. I empirically compare the forecasting performance of the dynamic factor model on various samples based on different selection criteria including my own. The forecasting exercise is performed for Turkish real GDP growth. My results show that the new sampling technique performs best as it attains first place in ranking for all backcast, nowcast and one-quarter ahead forecast periods.
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Performance, managerial skill and factor exposures in commodity trading advisors and managed futures funds
(2016-09) Avcı, Süreyya Burcu; Çağlayan, Mustafa Onur; Çağlayan, Mustafa Onur; Çeliker, U.; Güner, B.; Yücel, M. E.; Demiroğlu, C.; Department of Business; Avcı, Süreyya Burcu
Understanding risk is important. Prior to 2008, as the yields on safe assets hit rock bottom, investors turned their focus to an alphabet soup of more complex instruments. These complex securities were rated AAA, they appeared as safe as U.S. Treasuries, yet with much higher yields. The financial crisis of 2008 revealed that higher yields on these instruments in fact came with higher risk, albeit too late for these investors. The focus of this research is to understand the risk-return tradeoff in two financial instruments that have not been currently investigated, commodity trading advisors (CTAs) and managed futures funds (MFFs). This study starts with documenting the differences of CTAs and MFFs with hedge funds and mutual funds: We start with legal and operational differences. Next, performance analysis indicates that CTAs and MFFs, as stand-alone investment vehicles, provide higher returns than the average market returns in bear markets; while carrying a lower level of risk. CTAs' and MFFs' strong standing in bear markets let them deserve their so-called title "downside risk protectors." CTAs and MFFs are profitable individual assets, but addition of these funds to classical asset portfolios enhance portfolio performance significantly. This feature makes them strong hedging assets. As expected, in up markets, their performance is below standard asset performances. I find that the superior performance of CTAs and MFFs can be explained by managerial skill. Positive and significant Jensen alphas are evidence of good performance; moreover, persistence of Jensen alphas is supported by both parametric and non-parametric tests. Incentive fee and age of the fund are found to positively related to managerial skill; while somewhat surprisingly, management fee is found to be negatively related to managerial skill. I also find that many financial and macroeconomic factors are statistically unrelated to CTA and MFF performances. However, the value premium (HML) factor and industrial production growth (IPG) are correlated with the performance of these funds. HML has a positive effect on one-month-ahead fund returns whereas IPG has a negative effect on one-month-ahead fund returns. Nonparametric tests support these results marginally. These findings suggest that both CTAs and MFFs use well-known and well-established predictors of expected returns to generate their alphas. Keywords: Commodity trading advisors, managed futures funds, performance analysis,managerial skill, factor exposures.
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Quantifying the spillover of green products on consumer attitudes and umbrella brand sales
(2017-06) Özcan, Başar; Pauwels, Koen Hendrik; Pauwels, Koen Hendrik; Özsomer, A.; Soyer, Emre; Harmancıoğlu, N.; Gözübüyük, R.; Department of Business; Özcan, Başar
Despite growing consumer attention to the environment, it is still unclear how and how much companies benefit from their large investments in 'green' products. This paper quantifies the positive spillover of sustainable green products on the umbrella brand's other ('brown') product sales. The conceptual framework builds on halo effects, signalling and umbrella branding to develop hypotheses on attitude spillover and its conversion to higher brown product sales. The author tests this framework with data on Toyota Prius' first eight years of marketing mix, attitude metrics and sales. The vector autoregressive model shows significant improvement from incorporating green product attitude metrics in the sales forecasts for Toyota's other products. Not all brown products benefit from gains in Prius attitudes, only the less expensive brands do so. These results suggest interesting trade-offs between substitution effects and positive spillover effects of green products in an umbrella brand's portfolio.
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Robust estimation of term structure and implied volatility in emerging markets
(2016-07) Ahi, Emrah; Şener, Emrah; Şener, Emrah; Department of Business; Ahi, Emrah
Despite powerful advances in interest rate curve modeling for data-rich countries in the last 30 years, comparatively little attention has been paid to the key practicalproblem of estimation of the term structure of interest rates for emerging markets. This may be partly due to limited data availability. However, emerging bond markets are becoming increasingly important and liquid. It is, therefore, important to understand whether conclusions drawn from developed countries carry over to emerging markets. I estimate model parameters of fully exible Nelson Siegel Svensson term structures model which has become one of the most popular term structure model among academics, practitioners, and central bankers. I investigate four sets of bond data: U.S. Treasuries, and three major emerging market government bond data-sets (Brazil, Mexico and Turkey). I found that gradient and direct search methods perform poorly in estimating term structures of interest rates, while global optimization methods, particularly the hybrid particle swarm optimization, do well. Results are consistent across countries, both in- and out-of-sample, and for perturbations in prices and starting values. Another asset class I used the Nelson Siegel model is FX options where volatility smile for both emerging and developed markets is consistent with factor analysis in which three factor explains almost 100 % of the variation. I examine a number of models from literature to test whether they are consistent on the trading of options on the currencies from the over-the-counter market. I examine the in-sample and out-of-sample performance of the Nelson-Siegel model and found it has a superior performance when compared with benchmark models on FX options data set.
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The effects of climate on social media engagement
Turan, Işıl Büdeyri; Akçura, Münir Tolga; Akçura, Münir Tolga; Ataman, Mehmet Berk; Döğerlioğlu-Demir, Kıvılcım; Pauwels, Koen Hendrik; Sriram, S.; Graduate School of Business
User-generated content drives engagement, crucial for brand performance. Social media engagement is influenced by individual mood, preferences, and environmental cues, including temperature. Despite its impact, the specific influence of temperature on user engagement remains unclear. This thesis investigates temperature's impact on user engagement and its interaction with social media campaigns. The focus is on temperature due to its overwhelming influence on social media engagement compared to other climate variables such as cloudiness, air pressure, wind speed and humidity. Through a controlled experiment and empirical study spanning five and a half years, the research reveals several key findings: extremely high temperatures decrease user engagement by reducing happiness levels; high temperatures have a greater impact than low temperatures. The detrimental impact of high temperatures is significant on post creation, but not on liking, commenting, and sharing behaviors, indicating content creation behavior is more sensitive to high temperatures than content contribution behavior. A specific dataset composed of user-generated content quantifies the negative impact of high temperatures and shows that a social media campaign during extreme heat mitigates its adverse effects by only 36.7%; and campaign effectiveness decreases by 29.2% during extremely hot weather. This study is the first to comprehensively explore the effects of extreme temperatures on user engagement. The implications extend to researchers, social media managers, and campaign planners, providing insights for enhancing engagement strategies in varying temperature conditions.
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Three essays on the behavior of equity market returns
(2016-12) Lekpek, Senad; Kayaçetin, Nuri Volkan; Özsoy, Satı Mehmet; Kayaçetin, Nuri Volkan; Özsoy, Satı Mehmet; Yalçın, Atakan; Atılgan, Y.; Demirtaş, Ö.; Department of Business; Lekpek, Senad
The first chapter of this thesis analyzes return comovements phenomena known as correlation asymmetry. The phenomena has its two manifests: asymmetric correlations, referring to stock return correlations being higher during downside movements than during upside movements, and counter-cyclical correlations, referring to correlations being higher during recessions than during boom periods. We show that, unlike the asymmetric correlations, the counter-cyclical correlations are driven by the counter-cyclical market volatility. This finding has important implications for understanding the correlation risk as well as modeling correlation asymmetry. The next two chapters investigate the turn-of-the-month (ToM) effect, a pattern of high returns around month-ends: the second chapter examines the presence of the effect in the G7 equity markets, while the last chapter focuses on the ToM effect in the Turkish market. We show that the ToM effect is statistically and economically significant in all G7 equity markets over 1998-2015, and in the Turkish equity market over 1988-2015. The effect is stronger following months with (a) significant information inflow and (b) above average market return. We find that the effect strengthens in the U.S. and Canada and weakens in the U.K, Germany, France, Italy, and Japan in the latter half of the sample. The effect also gains importance in the Turkish equity market over the later subsamples. Estimating an e-GARCH model with daily index returns, we link the ToM effect to a decline in expected volatility in the days leading up to month-turns. These findings provide support for the information-risk hypothesis wherein the resolution of uncertainty towards reporting deadlines leads to a reduction in expected risk premiums, sending equity valuations up.

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