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This paper aims to propose a hybrid-forecasting model for long-term tourism demand forecasting. As such, it attempts to model the tourism demand in the Philippines, which is a relatively underrepresented area in the literature, despite its tourism sector’s growing economic progress.

A hybrid support vector regression (SVR) – seasonal autoregressive integrated moving averages (SARIMA) model is proposed to model the seasonal, linear and nonlinear components of the tourism demand in a destination country. The paper further proposes the use of multiple criteria decision-making (MCDM) approaches in selecting the best forecasting model among a set of considered models. As such, a preference ranking organization method for enrichment of evaluations (PROMETHEE) II is used to rank the considered forecasting models.

The proposed hybrid SVR-SARIMA model is the best performing model among a set of considered models in this paper using performance criteria that evaluate the errors of magnitude, directionality and trend change, of a forecasting model. Moreover, the use of the MCDM approach is found to be a relevant and prospective approach in selecting the best forecasting model among a set of models.

The novelty of this paper lies in several aspects. First, this paper pioneers the demonstration of the SVR-SARIMA model’s capability in forecasting long-term tourism demand. Second, this paper is the first to have proposed and demonstrated the use of an MCDM approach for performing model selection in forecasting. Finally, this paper is one of the very few papers to provide lenses on the current status of Philippine tourism demand.

With the aggressive movement towards testing for COVID-19 across the globe, this study aims to shed light on how testing facilities perform in an operational perspective.

With 102 testing facilities in the Philippines, the relative efficiencies of each facility are quantified using a data envelopment analysis technique. Afterwards, a best-worst method was conducted to assign priority weights to each testing facility.

Results show that the proposed approach effectively prioritizes testing facilities that most likely have high utilization.

The findings in this study would be significant to the literature in a number of respects. For one, it reveals results that would stimulate the interest among scholars in a wide variety of disciplines such as management, data mining, policymaking, decision science and epidemiology, among others.

This study differs from previous works in a number of respects, particularly, in that to the best of the authors’ knowledge, this is the first study to examine the relative efficiencies of COVID-19 testing facilities.

This paper aims to propose a new genetically evolved fuzzy cognitive mapping approach as a decision-making framework for analyzing the relationships between the drivers and strategies for green computing adoption.

A focus group discussion among stakeholders in the Philippines is used to establish the relationships between the drivers and strategies of green computing adoption.

The proposed approach significantly reduces the time complexity for developing the fuzzy cognitive maps and provides a basis for comprehensively clustering drivers and strategies that share similar characteristics.

This paper’s results provide insights into how the drivers and strategies of green computing adoption facilitate the intention of adopting stakeholders. Moreover, it provides a framework for analyzing structural relationships that exist between factors in a compliant manner.

To the best of the author’s knowledge, the paper is the first to analyze the drivers and strategies of green computing under a complex systems’ perspective. Moreover, this is the first study to offer lenses in a Philippine scenario.

This paper aims to propose a novel hybrid-decision-making trial and evaluation laboratory-K means clustering algorithm as a decision-making framework for analyzing the barriers of green computing adoption.

A literature review is conducted to extract relevant green computing barriers. An expert elicitation process is performed to finalize the barriers and to establish their corresponding interrelationships.

The proposed approach offers a comprehensive framework for modeling the barriers of green computing adoption.

The results of this paper provide insights on how the barriers of green computing adoption facilitate the adoption of stakeholders. Moreover, the paper provides a framework for analyzing the structural relationships that exist between factors in a tractable manner.

The paper is one of the very first attempts to analyze the barriers of green computing adoption. Furthermore, it is the first to offer lenses in a Philippine perspective. The paper offers a novel algorithm that can be useful in modeling the barriers of innovation, particularly, in green computing adoption.

Due to the growing dominance of the millennials in the secondhand clothing (SHC) market, it is crucial to understand the dynamics of their SHC buying behavior. Despite such significance, it has yet to be explored in the current literature. To address such a gap, this paper aims to explore the antecedents of the SHC buying behavior of millennials.

A purposive survey is conducted to establish relationships between the antecedents. As such, the interrelationships of the antecedents are modeled using the interpretative structural modeling (ISM) approach.

Results reveal that SHC antecedents exhibit several characteristics depending upon their characterization of being driving, dependence, linkage and autonomous variables.

This work pioneers the identification of SHC buying behavior antecedents specifically for the millennial market, as well as in the provision of a holistic analysis of the complex contextual relationships of these antecedents. The findings of this work provide insights that are crucial to the extant literature in developing theoretical frameworks and paradigms that help in understanding the dynamics of the SHC buying behavior. Moreover, such results are beneficial to marketing managers and practitioners in innovating their strategies to capture the millennial market better.