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Partial least squares structural equations modeling (PLS-SEM) uses sampling bootstrapping to calculate the significance of the model parameter estimates (e.g., path coefficients and outer loadings). However, when data are time series, as in marketing mix modeling, sampling bootstrapping shows inconsistencies that arise because the series has an autocorrelation structure and contains seasonal events, such as Christmas or Black Friday, especially in multichannel retailing, making the significance analysis of the PLS-SEM model unreliable. The alternative proposed in this research uses maximum entropy bootstrapping (meboot), a technique specifically designed for time series, which maintains the autocorrelation structure and preserves the occurrence over time of seasonal events or structural changes that occurred in the original series in the bootstrapped series. The results showed that meboot had superior performance than sampling bootstrapping in terms of the coherence of the bootstrapped data and the quality of the significance analysis.
Mariano Méndez-Suárez. Marketing Mix Modeling Using PLS-SEM, Bootstrapping the Model Coefficients. Mathematics 2021, 9, 1832 .
AMA StyleMariano Méndez-Suárez. Marketing Mix Modeling Using PLS-SEM, Bootstrapping the Model Coefficients. Mathematics. 2021; 9 (15):1832.
Chicago/Turabian StyleMariano Méndez-Suárez. 2021. "Marketing Mix Modeling Using PLS-SEM, Bootstrapping the Model Coefficients." Mathematics 9, no. 15: 1832.
Although for years the marketing science community has been actively proposing models for measuring the effectiveness and return on marketing investment (ROI), marketing attribution remains one of the major issues today. In fact, the Marketing Science Institute has identified attribution marketing as the number one priority since 2016. In this research we use the calibrated structural equations from a partial least squares model from previous research to estimate the impact of advertising on web and store sales for an omnichannel retailer of electronic consumer goods. From this model, as a novelty, the research derives the marketing metrics on percentage of sales attributable to each advertising channel, including, online, offline, paid search advertising and branded search queries. Finally, we present some managerial implications of our model. We find that not considering the simultaneous cross effects of the different advertising media, managers may make incorrect decisions inferring attribution from misleading calculations.
Mariano Méndez-Suárez; Abel Monfort. Marketing Attribution in Omnichannel Retailing. Advances in National Brand and Private Label Marketing 2021, 114 -120.
AMA StyleMariano Méndez-Suárez, Abel Monfort. Marketing Attribution in Omnichannel Retailing. Advances in National Brand and Private Label Marketing. 2021; ():114-120.
Chicago/Turabian StyleMariano Méndez-Suárez; Abel Monfort. 2021. "Marketing Attribution in Omnichannel Retailing." Advances in National Brand and Private Label Marketing , no. : 114-120.
This article investigates why banks maintain unprofitable customers by applying real options theory to determine their customer lifetime value (CLV) and assessing threshold values above which it is economically desirable to abandon those customers. The proposed valuation method is designed to enable a better understanding of the appraisal process, ensure greater transparency and account for the incremental value added by reputation as a summary of positive perceptions and recommendations about a brand. Using data on customers of a Spanish leading retail bank, the results show that banks act according to real options theory in their decisions to maintain apparently unprofitable customers, that optimal divesting points exist and that the incremental value of reputation may be isolated. The proposed methodology can help better elucidate banks’ decisions on customer management.
Mariano Méndez-Suárez; Natividad Crespo-Tejero. Why do banks retain unprofitable customers? A customer lifetime value real options approach. Journal of Business Research 2020, 122, 621 -626.
AMA StyleMariano Méndez-Suárez, Natividad Crespo-Tejero. Why do banks retain unprofitable customers? A customer lifetime value real options approach. Journal of Business Research. 2020; 122 ():621-626.
Chicago/Turabian StyleMariano Méndez-Suárez; Natividad Crespo-Tejero. 2020. "Why do banks retain unprofitable customers? A customer lifetime value real options approach." Journal of Business Research 122, no. : 621-626.
(1) Social Impact Bonds (SIBs) foster the relationships between public and private sectors while adding value to new forms of investment that are closely linked to Socially Responsible Investments (SRIs). In this context, Sustainable Developments Goals (SDGs) aim to strengthen global partnerships in order to achieve the 2030 Agenda. Sustainable banking should consider its role in both new responsible investment products and the 2030 Agenda. This study aims to: (i) estimate the ROI of SIBS, (ii) define a financial formulation and a measurement system, and (iii) explain the relationship between SIBs and SDGs. (2) This research analyzes SIBs from an SDG approach, and proposes a valuation model based on a financial options valuation methodology that clarifies the financial value of the world’s first SIB (Peterborough Prison, UK). (3) Findings suggest that investors expect to have a negative return of 16.48%, and that this expected loss may be compensated for by the short- and long-term positive impact of an intervention in society. (4) It is shown that SIBs provide an opportunity to reach SDG 17 and improve sustainable investment portfolios, while providing an opportunity to strengthen a company’s Corporate Social Responsibility policy and its corporate reputation.
Mariano Méndez-Suárez; Abel Monfort; Fernando Gallardo. Sustainable Banking: New Forms of Investing under the Umbrella of the 2030 Agenda. Sustainability 2020, 12, 2096 .
AMA StyleMariano Méndez-Suárez, Abel Monfort, Fernando Gallardo. Sustainable Banking: New Forms of Investing under the Umbrella of the 2030 Agenda. Sustainability. 2020; 12 (5):2096.
Chicago/Turabian StyleMariano Méndez-Suárez; Abel Monfort; Fernando Gallardo. 2020. "Sustainable Banking: New Forms of Investing under the Umbrella of the 2030 Agenda." Sustainability 12, no. 5: 2096.
This article investigates the effect of online advertising (display, retargeting, social media and paid search) and offline advertising (TV and store flyers) on conducting branded search queries and the mediating role of these queries on web and store sales. Findings show that online and offline advertising increase consumers’ propensity to conduct branded search queries and that branded search queries combined with paid search advertising are the most relevant variables to generate sales on the web or in store in multi-channel retailing. Results have implications on the design of multi-channel communication campaigns. This study employs a partial least squares structural equation model (PLS-SEM), with data from a European electronic consumer multi-channel retailer, to measure simultaneously the total effect of online and offline advertising on sales mediated by branded queries and paid search advertising.
Mariano Méndez-Suárez; Abel Monfort. The amplifying effect of branded queries on advertising in multi-channel retailing. Journal of Business Research 2019, 112, 254 -260.
AMA StyleMariano Méndez-Suárez, Abel Monfort. The amplifying effect of branded queries on advertising in multi-channel retailing. Journal of Business Research. 2019; 112 ():254-260.
Chicago/Turabian StyleMariano Méndez-Suárez; Abel Monfort. 2019. "The amplifying effect of branded queries on advertising in multi-channel retailing." Journal of Business Research 112, no. : 254-260.
Financial innovation by means of Fintech firms is one of the more disruptive business model innovations from the latest years. Specifically, in the financial advisor sector, worldwide assets under management of artificial intelligence (AI)-based investment firms, or robo-advisors, currently amount to US$975.5 B. Since 2008, robo-advisors have evolved from passive advising to active data-driven investment management, requiring AI models capable of predicting financial asset prices on time to switch positions. In this research, an artificial neural network modelling framework is specifically designed to be used as an active data-driven robo-advisor due to its ability to forecast with today’s copper prices five days ahead of changes in prices using input data that can be fed automatically in the model. The model, tested using data of the two periods with a higher volatility of the returns of the recent history of copper prices (May 2006 to September 2008 and September 2008 to September 2010) showed that the method is capable of predicting in-sample and out-of-sample prices and consequently changes in prices with high levels of accuracy. Additionally, with a 24-day window of out-of-sample data, a trading simulation exercise was performed, consisting of staying long if the model predicts a rise in price or switching to a short position if the model predicts a decrease in price, and comparing the results with the passive strategies, buy and hold or sell and hold. The results obtained seem promising in terms of both statistical and trading metrics. Our contribution is twofold: 1) we propose a set of input variables based on financial theory that can be collected and fed automatically by the algorithm. 2) We generate predictions five days in advance that can be used to reposition the portfolio in active investment strategies.
Mariano Méndez-Suárez; Francisco García-Fernández; Fernando Gallardo. Artificial Intelligence Modelling Framework for Financial Automated Advising in the Copper Market. Journal of Open Innovation: Technology, Market, and Complexity 2019, 5, 81 .
AMA StyleMariano Méndez-Suárez, Francisco García-Fernández, Fernando Gallardo. Artificial Intelligence Modelling Framework for Financial Automated Advising in the Copper Market. Journal of Open Innovation: Technology, Market, and Complexity. 2019; 5 (4):81.
Chicago/Turabian StyleMariano Méndez-Suárez; Francisco García-Fernández; Fernando Gallardo. 2019. "Artificial Intelligence Modelling Framework for Financial Automated Advising in the Copper Market." Journal of Open Innovation: Technology, Market, and Complexity 5, no. 4: 81.
Eduardo Hernández-Varas; Francisco J Labrador Encinas; Mariano Méndez-Suárez. Psychological capital, work satisfaction and health self-perception as predictors of psychological wellbeing in military personnel. 2019, 31, 277 -283.
AMA StyleEduardo Hernández-Varas, Francisco J Labrador Encinas, Mariano Méndez-Suárez. Psychological capital, work satisfaction and health self-perception as predictors of psychological wellbeing in military personnel. . 2019; 31 (3):277-283.
Chicago/Turabian StyleEduardo Hernández-Varas; Francisco J Labrador Encinas; Mariano Méndez-Suárez. 2019. "Psychological capital, work satisfaction and health self-perception as predictors of psychological wellbeing in military personnel." 31, no. 3: 277-283.
Mariano Méndez-Suárez; Prosper Lamothe Fernandez. Commodities Prices Modeling Using Gaussian Poisson-Exponential Stochastic Processes, A Practical Implementation In The Case Of Copper. ECMS 2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel Pedrera 2009, 1 .
AMA StyleMariano Méndez-Suárez, Prosper Lamothe Fernandez. Commodities Prices Modeling Using Gaussian Poisson-Exponential Stochastic Processes, A Practical Implementation In The Case Of Copper. ECMS 2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel Pedrera. 2009; ():1.
Chicago/Turabian StyleMariano Méndez-Suárez; Prosper Lamothe Fernandez. 2009. "Commodities Prices Modeling Using Gaussian Poisson-Exponential Stochastic Processes, A Practical Implementation In The Case Of Copper." ECMS 2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel Pedrera , no. : 1.