Real-world Market Research Articles

Sustainable trade promotion decisions under demand disruption in manufacturer-retailer supply chains

Trade promotion plays a critical role in real-world marketing and operations management. However, previous research paid rare attention to how to provide trade promotions in a sustainable manner when consumer demand is disrupted. Considering that demand disruption is becoming surging because of the digital economy, it is quite necessary to discern the managerial implications for sustainable trade promotion practice in demand disruption scenarios. For this purpose, we analyze trade promotions under demand disruption by integrating demand uncertainty and limited capacity into a stylized demand disruption model. Three trade promotion types, i.e. off-invoice, scan-back, and revenue-sharing, are examined, and optimal promotion decisions are derived for each strategy. Our results show that both manufacturer and retailer would adopt aggressive pricing strategies as the demand disruption being intensified. For trade promotion strategies, our results show that, for a certain level of demand disruption, the manufacturer prefers off-invoice rather than revenue-sharing when the manufacturer needs to offer a more aggressive trade promotion. This result indicates that, when aggressive trade promotions are needed, the manufacturer may be worse off by a revenue-sharing strategy, even though the revenue-sharing could coordinate a supply chain.

Active viral marketing: Incorporating continuous active seeding efforts into the diffusion model

Existing viral-marketing network models commonly assume a preliminary phase in which a marketer actively infects a subset of social network’s users, represented by nodes, followed by a passive viral process, in which nodes infect other nodes without external intervention. However, in real-world commercial scenarios, substantial efforts are often invested by companies to promote their products, suggesting that the adoption of products is rarely the consequence of a viral spread alone.Under this observation, this paper proposes a new diffusion model, named Active Viral Marketing, which better fits real-world marketing scenarios, where adoption of products relies on continuous active promotion efforts by the marketer. In the proposed model, the success of a marketing attempt to infect a potential customer (uninfected node), depends on the number of adopting friends (infected neighbors) of this user, assuming a user is more likely to adopt a product if more of his/her friends have already adopted it, while taking into account that social influence diminishes over time due to a memory-loss effect.The paper further proposes a set of heuristics to schedule the marketing attempts. The main idea behind these heuristics is to utilize the information on the dynamic adoption-states of neighbor nodes, in addition to the static social network topology, when choosing the next node to seed. An extensive experimentation demonstrates how the proposed seeding heuristics improve the adoption rate of products by 30%–75% in comparison to existing state-of-the-art methods that mainly rely on the network topology.

Quanto Option Pricing with Lévy Models

We develop a multivariate Levy model for the pricing of quanto options that captures three characteristics observed in real-world market for stock prices and currencies: jumps, heavy tails and skewness. The model is developed by using a bottom-up approach from a subordinator. We do so by replacing the time of a Brownian motion with a non-decreasing Levy process, rapidly decreasing subordinator. We refer to this model as a multivariate rapidly decreasing Levy process. We consider two benchmarks: Black-Scholes and normal tempered stable process, the later constructed using a classical tempered stable subordinator. We then compare using a time series of daily log-returns and market prices of European-style quanto options the relative performance of the rapidly decreasing Levy process to that of Black-Scholes and the normal tempered stable process. We find that the proposed modeling process is superior to the other two processes for pricing quanto options.

Who gets my flex? An evolutionary game theory analysis of flexibility market dynamics

Maintaining a real time balance between energy consumption and production is challenging when faced with increasing penetration of Renewable Energy Sources (RES) because of the increased variability in generation output. Demand-Side Management (DSM) techniques address this issue by steering consumers’ energy off-take, thereby enabling further penetration of RES. Present paper addresses the problem of overproduction from distribution grid connected wind generation. We present and analyze two business cases in the Belgian-European energy landscape for using upward consumption flexibility to deal with excessive wind power injection. We focus on the perspective of the flexibility providers and the strategic choice they face in choosing the business partner that maximizes their expected financial compensation. Evolutionary game theory is used to model this strategic choice and to provide a framework for quantifying realistic financial compensation bounds based on real world market and wind production data for multiple locations in Belgium. Results show that in a competitive market setting compensation payments for flexible power consumption are higher when dealing with higher wind forecast error levels. These results validate the economic benefits of having accurate wind production forecasts.

A hybrid probabilistic fuzzy ARIMA model for consumption forecasting in commodity markets

Consumption forecasting is a critical issue in commodity markets on which financial decision-makers depend for accuracy. To adequately handle the complexity and uncertainty associated with real-world market problems, forecasting needs to be capable of handling complex situations. The steel industry is a strategic one for Iran playing a critical role in the national economy. Using time series models, this study aims to forecast the future trend of Iran’s crude steel consumption. Although autoregressive integrated moving average (ARIMA) models are regarded as the most important time series models and are extensively employed in forecasting financial markets, they are hampered by certain limitations that detract from their popularity. They are based on the assumption that a linear relationship holds between future values of a time series and its current and past values. Moreover, they depend heavily on a large amount of historical data to provide the desired results. To overcome the limitations in such conventional models, fuzzy autoregressive integrated moving average models have been proposed as improved versions of the ARIMA models. Unfortunately, the former are also plagued by very wide forecasted intervals in cases where there are outliers that create instability in the data. The present paper proposes a hybrid model which is a combination of computational intelligence tools and soft computing techniques. In such a form they take advantage of their unique properties which, when exploited, can provide more accurate financial forecasts. The main objective of the proposed model is to identify nonlinear patterns with probabilistic classifiers to obtain narrower intervals than would be otherwise possible under the traditional FARIMA models. The empirical results obtained from applying the proposed model to forecasting Iran’s steel consumption provide significantly improved accuracy.

Heuristic Thinking in the Market for Online Subscriptions

I study “left-digit bias” (LDB) in which consumers perceive products as discretely more expensive when the left-hand digit of the price increases, for example when comparing products priced at $5.99 vs. $6.00, $19 vs. $20, or $195 vs. $200. Recent work has established the presence of LDB in large-scale, real-world market settings including used car odometer readings (Lacetera et. al 2012) and grocery store prices under $10 (Shlain 2018). I leverage new data covering online subscription sales at more than 100,000 firms over six years to document similar patterns in all digits of prices (dollars, tens of dollars, hundreds of dollars) for subscriptions priced up to $1,000. Using panel data methods to reduce selection bias suggests potential revenue gains of several percentage points from optimal repricing, consistent with Shlain (2018). I discuss implications of potential large-scale pricing assistance for the online economy.

Markets, trust and cultural biases: evidence from eBay

A body of research argues that cultural biases in trust may be responsible for economic backwardness. This paper studies the role of cultural biases in a real-world market, eBay, with well-designed features intended to facilitate cooperation. We analyze the buyer’s decision to leave negative feedback as an act of mistrust towards the seller. To identify the effects of buyer characteristics on feedback choices, we exploit an identification strategy that leverages high-volume data from millions of transactions. We find that negative feedback decreases as buyers gain experience on the market. Also, we show that measures of pro-social beliefs and behavior do not explain feedback choices. Our favorite interpretation is that cultural biases in trust may have limited importance in markets with effective reputation-building mechanisms.

Price competition or price leadership

Every now and then, we observe a fierce price war in a real world market, through which competing firms, selling a homogenous product, end up with Bertrand-like price competition. Despite this, not much has been known in the existing literature as to why a price competition market is formed. We address this question in the context of a choice between engaging in price competition and holding a price leader. Focusing on a duopoly market, we demonstrate that if the market is tight (or if the relative size of demand to supply exceeds a threshold value) and if the cost differential between firms is reasonably large, duopoly firms choose to engage in price competition. Otherwise, one firm becomes a price leader while the other firm a price follower.

Young adult non-smokers\u2019 exposure to real-world tobacco marketing: results of an ecological momentary assessment pilot study

BackgroundThe aims of this pilot study were to assess and characterize non-current smoking young adults’ exposure to tobacco marketing through an ecological momentary assessment protocol.MethodsEcological momentary assessment (EMA) consists of repeated measurement of momentary phenomena and is well-suited to capture sporadic experiences in the real-world, such as exposure to tobacco marketing. EMA has the potential to capture detailed information about real-world marketing exposures in ways that reduce recall bias and increase ecological validity. In this study, young adults (n = 31; ages 18–25) responded to random prompts regarding their momentary exposure to tobacco marketing via text messages on their smartphones for 14 days (n = 1798 observations). Unadjusted and adjusted analyses were conducted using multilevel logistic regression to assess the odds of exposure accounting for correlation of multiple repeated measures within individuals while controlling for variability between individuals.ResultsRespondents reported, on average, two momentary exposures to tobacco advertising in the 14-day study period. In adjusted analyses, African–American (aOR 3.36; 95% CI 1.07, 10.54) and Hispanic respondents (aOR 5.08; 95% CI 1.28, 20.13) were more likely to report exposure to tobacco advertising. Respondents were also more likely to report exposure when also exposed to others using tobacco products and when they were at stores compared with at home (aOR 14.82; 95% CI 3.61, 60.88).ConclusionNon-smoking young adults report exposure to tobacco marketing particularly at the point-of-sale, with the highest likelihood of exposure among African-American and Hispanic young people. EMA protocols can be effective in assessing the potential impact of point-of-sale tobacco marketing on young adults.

The potential of anime for destination marketing: fantasies, otaku, and the kidult segment

While a substantial body of literature exists on film tourism, there is a lack of research attention bridging the potential of Japanese anime on real-world destination marketing. The implications of anime tourism can extend far beyond geographic boundary as the worldwide anime market is diversifying, providing novel opportunities for destination marketing organizations in other countries. To address this research gap, this paper first defines anime versus animated films to clarify the definition of anime for the tourism literature, and then draws out theoretical differences between the two types of entertainment within a cinematic perspective to highlight their conceptual boundaries across place, protagonist, and production. This paper suggests that the ways in which these three aspects are manifested in anime versus films are very different: anime settings are more fantasy-orientated than most films; viewers develop their self-identity (i.e. as an ‘otaku’) during childhood and adolescence; and anime productions can be extended with new series to create more enduring engagement to develop the kidult segment. This paper contributes to the literature by connecting the aforementioned cinematic aspects as a basis for elaboration of how differences among the three dimensions could be directly related to potential destination marketing activities.

Effects of correlations and fees in random multiplicative environments: Implications for portfolio management.

Geometric Brownian motion (GBM) is frequently used to model price dynamics of financial assets, and a weighted average of multiple GBMs is commonly used to model a financial portfolio. Diversified portfolios can lead to an increased exponential growth compared to a single asset by effectively reducing the effective noise. The sum of GBM processes is no longer a log-normal process and has a complex statistical properties. The nonergodicity of the weighted average process results in constant degradation of the exponential growth from the ensemble average toward the time average. One way to stay closer to the ensemble average is to maintain a balanced portfolio: keep the relative weights of the different assets constant over time. To keep these proportions constant, whenever assets values change, it is necessary to rebalance their relative weights, exposing this strategy to fees (transaction costs). Two strategies that were suggested in the past for cases that involve fees are rebalance the portfolio periodically and rebalance it in a partial way. In this paper, we study these two strategies in the presence of correlations and fees. We show that using periodic and partial rebalance strategies, it is possible to maintain a steady exponential growth while minimizing the losses due to fees. We also demonstrate how these redistribution strategies perform in a phenomenal way on real-world market data, despite the fact that not all assumptions of the model hold in these real-world systems. Our results have important implications for stochastic dynamics in general and to portfolio management in particular, as we show that there is a superior alternative to the common buy-and-hold strategy, even in the presence of correlations and fees.

Measuring Trust with Market Data

A body of research argues that cultural biases in trust may be responsible for economic backwardness. This paper studies the role of cultural biases in a real-world market, eBay, with well-designed features intended to facilitate cooperation. We analyze the buyer’s decision to leave negative feedback as an act of mistrust towards the seller. To identify the effects of buyer characteristics on feedback choices, we exploit an identification strategy that leverages high-volume data from millions of transactions. We find that negative feedback decreases as buyers gain experience on the market. Also, we show that measures of pro-social beliefs and behavior do not explain feedback choices. Our favorite interpretation is that cultural biases in trust may have limited importance in markets with effective reputation-building mechanisms.

Quanto Option Pricing with LLvy Models

We develop a multivariate Levy model for the pricing of quanto options that captures three characteristics observed in real-world market for stock prices and currencies: jumps, heavy tails and skewness. The model is developed by using a bottom-up approach from a subordinator. We do so by replacing the time of a Brownian motion with a non-decreasing Levy process, rapidly decreasing subordinator. We refer to this model as a multivariate rapidly decreasing Levy process. We consider two benchmarks: Black-Scholes and normal tempered stable process, the later constructed using a classical tempered stable subordinator. We then compare using a time series of daily log-returns and market prices of European-style quanto options the relative performance of the rapidly decreasing Levy process to that of Black-Scholes and the normal tempered stable process. We find that the proposed modeling process is superior to the other two processes for pricing quanto options.

The BuzzFeed Marketing Challenge: An Integrative Social Media Experience

This article presents the BuzzFeed Marketing Challenge, which helps students gain integrative real-world marketing experience by selecting a target market, then creating, publishing, and promoting an article for the target market on entertainment publisher BuzzFeed.com. The challenge is for students to effectively use marketing strategy and consumer behavior principles to generate 1,000 article views in one week. The project provides each student with a personal case study that incorporates new product development, social media, analytics, and campaign management. The BuzzFeed Marketing Challenge is highly adaptable with undergraduate marketing and online MBA students reporting a breadth of positive learning outcomes.

Risk Modelling of Agricultural Products

In the real world market, agricultural commodity are imposed with fluctuating prices. This means that the price of agricultural products are relatively volatile, which means that agricultural business is a quite risky business for farmers. This paper presents some mathematical models to model such risks in the form of its volatility, based on certain assumptions. The proposed models are time varying volatility model, as well as time varying volatility with mean reversion and with seasonal mean equation models. Implementation on empirical data show that agricultural products are indeed risky.

INTERMITTENT BEHAVIOR INDUCED BY ASYNCHRONOUS INTERACTIONS IN A CONTINUOUS DOUBLE AUCTION MODEL

Continuous asynchronous trading activity is a key to understanding real-world market behavior. However, it is not easy to implement an agent-based computational market model because of the ambiguity between time and space. In this study, we use a model of asynchrony in a continuous double auction market in the form of noise and order restrictions to link inside- and outside- uncertainties in the economic system. Our model shows intermittent behavior with a small parameter value, which leads to the misapplication of the price-update rule, and consequently drives burst behavior. The statistical property of time development shows a similar tendency to that in previous empirical studies. Thus, it demonstrates the relationship between the asynchronous property and the complexity of economic systems.

Sugar Daddy: Quotas and the U.S. Government

Since 1981, the U.S. federal government has operated a price support program to help sugar beet and sugar cane producers and processors. This complex program works through a combination of loans, import quotas, and duties. As a result, sugar prices in the United States are significantly higher than world prices. For example, in December 2001, U.S. consumers paid 22.9 cents per pound, while the world price was just 9 cents per pound. The General Accounting Office estimates that the total cost to consumers is $1.9 billion a year. Uses a simple demand-and-supply framework with real-world data to assess the economic and political consequences of the U.S. sugar program.To illustrate welfare concepts such as consumer surplus, producer surplus, and dead-weight loss in a concrete, real-world market context.

Choosing schools, choosing selves: exploring the influence of parental identity and biography on the school choice process in Delhi, India

Drawing on qualitative interview data from a group of lower income parents in Delhi, India, this paper focuses on the dynamic relationship between parental choice of a particular school and parents’ own identity construction. The data indicate that choice of school is for some parents a symbolic expression of identity, influenced by family dynamics and parents’ educational biographies. The paper outlines the concept of ‘forging solidarities’ and proposes it as an alternative way of understanding school enrolment decisions that recognises the social significance of such choices for the wider family unit. More generally, as school choice mechanisms in various forms become an increasingly important part of the educational landscape in many countries, the findings draw attention to the sociocultural nature of choice in real-world market settings and the contribution of schooling choices to processes of social and educational segregation.

Distinguishing between endogenous and exogenous price volatility in food security assessment: An empirical nonlinear dynamics approach

We propose an empirical scheme—based on nonlinear dynamics—for diagnosing real-world market dynamics from observed price series data. The scheme distinguishes between endogenous and exogenous volatility in observed price series, tests whether endogenous volatility is generated by low-dimensional deterministic market dynamics, simulates these dynamics with a phenomenological market model, and models extreme volatility probabilistically. These diagnostics allow policymakers to make an empirically-informed determination of whether laissez-faire or interventionist policies are most promising in reducing price volatility in particular cases. We apply the diagnostic scheme to provide compelling empirical evidence that observed volatility in organic apple, pear, orange, and lemon prices at the Milano (Italy) Ipercoop is due to endogenous market dynamics governed by low-dimensional nonlinear behavior. The implication for food policy is that this inherently unstable market cannot be relied upon to systematically stabilize observed price volatility from random exogenous shocks. There may be scope for public interventions targeted to increasing the flexibility of organic fruit producers in responding to changing market conditions.

Derivatives Valuation Based on Arbitrage: The Trade is Crucial

Derivatives valuation has strong theoretical support because models are derived from the principle that arbitrage between the derivative and its underlying will eliminate riskless profits and drive the market price to the model value. “No‐arbitrage” is invoked routinely whenever a new pricing model is developed. But real world market prices are determined by trades, not by theories. In this talk, I discuss how different the arbitrage trade is for different markets and different models and I review articles from the literature that illustrate how limits to the arbitrage trade have affected the way derivatives theory gets into prices in practice. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:316–327, 2017