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Purpose 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. Design/methodology/approach 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. Findings Results reveal that SHC antecedents exhibit several characteristics depending upon their characterization of being driving, dependence, linkage and autonomous variables. Originality/value 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.

Current literature merely identifies the driving factors of research productivity in higher education institutions without directly examining their interrelationships that would offer some fundamental insights into the nature of these factors. Thus, this work intends to identify those driving factors and establish their structural relationships to determine those factors with crucial roles in advancing research productivity. Due to the subjectivity of the identified driving factors and the notion that the evaluation of their relationships reflects an expert judgment, an interpretive structural modeling (ISM) approach and the Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis were adopted. Results show that institutional support, reward system, research funding, mentoring, and electronic information resources are the most crucial factors influencing research productivity. When addressed, these driving factors would motivate other driving factors, contributing to higher research productivity. In particular, these findings encourage higher education institutions to (1) efficiently allocate research funds and design mentoring programs, (2) offer efficient research incentive schemes, (3) develop initiatives that would support promising research proposals beneficial to the institution, and (4) collaborate with external organizations to grant funding for research proposals. These results contribute significantly to the literature as it provides meaningful insights that aid decision-makers in higher education institutions in resource allocation decisions, policy-making, and the design of efficient initiatives for augmenting their innovation potential.

During pandemics and outbreaks, the prevalence of fear among tourists reduces travel interests. To gradually reopen the tourism industry, subscribing to domestic tourism is a crucial mitigation strategy. Although an important agenda, evaluating the perceived degree of exposure of tourists to COVID-19 in tourist sites functioning under the domestic tourism initiatives has not been explored in the emerging literature. Thus, this work addresses this problem domain by proposing the use of TOPSIS-Sorta recently introduced multiple criteria sorting method. To demonstrate such an application, 20 tourist sites in a central Philippine province are evaluated under six attributes that define exposure to COVID-19. With 208 survey participants, results show that 12 sites are assigned to the 'moderate exposure' class, and eight under the 'high exposure' class, with no tourist site assigned to the 'low exposure' class. The proposed approach offers primary stakeholders (i.e. government, tourist operators, and tourists) a decision support tool in view of tourism recovery.

Purpose This study aims to draw observations on the current status and potentials of the Philippines as a farm tourism destination and identify the underlying factors that inhibit farm tourism development. It intends to gauge the challenges that Filipino farmers face in diversifying farms and operating farm sites and uses these challenges in crafting strategies and policies for relevant stakeholders. It also provides Philippine farm tourism literature to address the limitations of references in the topic. Design/methodology/approach The study adopts an exploratory type of inquiry method and secondary data collection from various sources, such as published journal articles, news articles and reports, to gain insights and relevant information on farm tourism. The study also uses a threats, opportunities, weaknesses and strengths analysis approach to develop competitive farm tourism strategies. Findings The Philippines, with vast agricultural land, has the necessary base for farm tourism, and the enactment of the Farm Tourism Development Act of 2016 bridges this potential. With low agricultural outputs, the country draws relevance for farm tourism as a farm diversification strategy to supplement income in rural communities. While having these potentials, crucial initiatives in physical characteristics, product development, education and training, management and entrepreneurship, marketing and customer relations and government support must be implemented. Farmers' lack of skills, training and capital investment potential to convert their farms into farm tourism sites serves as the major drawback. Thus, developing entrepreneurial and hospitality skills is crucial. Originality/value This work presents a historical narrative of initiatives and measures of the Philippine farm tourism sector. It also provides a holistic discussion and in-depth analysis of the current state, potentials, strategies and forward insights for farm tourism development.

Due to a considerable number of tourists coming in, the festival tourism industry faces environmental issues. With several stakeholders in the decision-making process at various levels of influence, coupled with the seasonality component of festivals, the complexity of managing these emerging environmental concerns exacerbates. This work contributes to the emerging literature of greening festival management by illustrating a case study of the Sinulog festival – one of the grandest festivals in the Philippines. The conditions experienced by the festival organization resonates with most festivals, at least in the Philippines. This case study assesses the compliance of the festival organization towards green management using the PDCA cycle. From those analyses, the findings show that the operations of the festival organization lack the green management agenda, and their view of such an agenda is myopic. The insights of the case, which also reflect most festivals, are crucial to green festival management.

Despite the rigid public safety protocols of the restaurant sector amid the COVID-19 pandemic in an effort to restart economic activities, customers do not feel secure eating at a sit-in restaurant, which is associated with prolonged restrictions on movement. As a mitigating initiative, holistically evaluating customers’ perceived degree of exposure to COVID-19 in restaurants is deemed relevant in the design of mitigation measures. Such an agenda is associated with multiple attributes under decision-making uncertainty within the framework of multiple criteria sorting (MCS). Thus, this work addresses this problem domain by proposing an intuitionistic fuzzy set extension of the previously developed TOPSIS-Sort (i.e., IF TOPSIS-Sort). As a case demonstration, 40 restaurants are evaluated under six attributes that define exposure to COVID-19. With 250 survey participants, the IF TOPSIS-Sort assigns 10, 13, and 17 restaurants to low, moderate, and high exposure classes, respectively. With this classification, crucial insights are offered to the restaurant industry for planning and policy formulation. To determine its effectiveness, a comparative analysis was carried with other distance-based MCS methods. Findings reveal that the proposed method is pessimistic and that other methods tend to underestimate the assignments, which may be counterintuitive, especially in applications related to public health. These sorting differences may be associated with addressing the vagueness and uncertainty in decision-making within the IF TOPSIS-Sort platform. The proposed novel IF TOPSIS-Sort is sufficiently generic for other domain sorting applications and contributes to the MCS literature.

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