One-Star Hotel Selection for Staycation using Simple Additive Weighting and Rank Order Centroid
Yerik Afrianto Singgalen
Faculty of Business Administration and Communication, Tourism Study Program, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
Email: [email protected]
Correspondence Author Email: [email protected]
Abstract−The development of the hospitality industry provides many choices to staycation enthusiasts in choosing the right accommodation service. Accommodation service providers also increase competitiveness through excellent service to the addition of facilities to adjust guest preferences and increase sales. The primary objective of this study is to analyze the decision- making behavior associated with choosing one-star hotels for a staycation. The research investigates the decision-making patterns in the context of one-star hotel stays for recreational purposes. The study utilizes the SAW method to evaluate the criteria of facilities, services, rating, cleanliness, value for money, and location, employing Rank Order Centroid (ROC) weighting. In light of the computations using Rank Order Centroid, it is discerned that the weights assigned to the criteria are as follows: W1 with a weight of 0.4083, w2 with a weight of 0.2416, w3 with a weight of 0.1583, w4 with a weight of 0.1027, w5 with a weight of 0.0611, and w6 with a weight of 0.0277. The research findings reveal the aggregation of weighted scores and ranking of alternatives, delineating that A4 attains the first rank with a value of 0.97395, followed by A3, securing the second rank with a value of 0.96511, and A1 acquires the third rank with a value of 0.95191. Thus, the significance of the identified alternative is that it sheds light on its superior performance according to the specified criteria. In conclusion, this research contributes valuable insights into the decision-making dynamics of staycation enthusiasts, pinpointing alternative A4 as the most favorable choice within one-star hotel accommodations.
Keywords: SAW; ROC; One-Star Hotel; Staycation
1. INTRODUCTION
Hotels play a pivotal role in advancing the tourism industry; hence, a comprehensive examination of consumer purchasing behavior in the context of accommodation services becomes imperative [1]. The inherent significance of hotels in shaping the landscape of tourism is underscored by their crucial role in providing lodgings for travelers, impacting the overall experience and satisfaction of tourists [2]. Consequently, a meticulous study of the behavioral patterns associated with acquiring accommodation services is essential [3]. Understanding how consumers make decisions regarding their lodging choices is imperative for industry stakeholders, as it allows for tailoring services to meet evolving preferences and expectations [4]. In essence, such research contributes to informed decision- making within the hospitality sector, thereby influencing strategic initiatives that further enhance the overall development and sustainability of the tourism industry.
Guest perceptions regarding the facilities and services within a hotel significantly impact the hotel's overall rating, leading to the assertion that studies on hotels are contextual and exhibit variations in their scope based on the hotel's star rating [5]. The contextual nature of hotel studies indicates that the considerations and discussions within such research endeavors are contingent upon the specific star rating of the hotel under examination [6]. This observation acknowledges the multifaceted nature of the hospitality industry, recognizing that the significance attributed to facilities and services may differ based on the perceived quality associated with different star ratings [7]. In conclusion, this acknowledgment prompts a nuanced understanding of hotel research, emphasizing the necessity to tailor inquiries according to specific star categories' distinctive characteristics and expectations.
The primary aim of this investigation is to analyze the Simple Additive Weighting (SAW) decision-making model within the context of selecting a one-star hotel for a staycation. The focal point of this study centers on comprehending the application and effectiveness of the SAW model specifically tailored to the criteria for choosing one-star accommodations for recreational stays [8]. The subsequent exploration of the intricacies inherent in the SAW model's decision-making process sheds light on its pertinent role, elucidating its potential contributions to selecting suitable staycation accommodations [9]. This research provides a balanced perspective on the significance of employing the SAW model, scrutinizing its potential advantages and drawbacks in hotel selection for staycation [10]. In conclusion, this research encapsulates its primary objective by assessing the efficacy of the SAW model in the decision-making landscape, particularly within the unique realm of selecting one-star hotels for staycations [11].
The significance of this research is underscored by the imperative needs of staycation enthusiasts who prioritize cost considerations as their foremost criterion [12]. In the contemporary travel landscape, economic considerations take precedence. The field has a burgeoning demographic of travelers seeking recreational stays within one-star hotels [13]. The primary objective of this study is to cater to the discerning requirements of this specific group, exploring the intricacies of staycation preferences within the framework of one-star accommodations [14]. An evaluative perspective is essential to understand the nuanced interplay between cost considerations and the staycation experience, thereby informing the development of tailored strategies for the hospitality industry [15]. In conclusion, this research addresses a critical gap in understanding the staycation
phenomenon, emphasizing the significance of cost factors in the decision-making process of those inclined towards one-star hotel accommodations for their recreational sojourns [16].
Previous studies have indicated the existence of similar topics employing the Simple Additive Weighting (SAW) decision support model in selecting hotels, destinations, and transportation services [17]. Despite this, the current research introduces a distinctive dimension by focusing on the context of staycation enthusiasts who prefer one-star hotels [18]. The overarching theme of these investigations shares a common ground in utilizing the SAW model for decision-making; however, this study diverges in its emphasis on the distinct criteria and analyses pertinent to the peculiar preferences of staycation aficionados opting for one-star accommodations [19]. The nuanced differences in these criteria and analyses underscore the unique characteristics of the staycation context, thereby contributing novel insights to the existing body of research in the field [20]. In conclusion, this study aligns with prior research methodologies and augments the scholarly discourse by delving into the specific considerations of one-star hotel selection within the staycation phenomenon [21].
The scope of this research is delimited by specific constraints, notably that the hotel selection context is not general but is confined to one-star hotels within the realm of staycation. Acknowledging the inherent differences in the decision-making criteria and considerations between one-star hotels and establishments of higher ratings and those within the broader tourism context Field [15] is crucial. While this circumscribed focus enhances the study's depth in analyzing the peculiarities of one-star staycation experiences, it simultaneously restricts the generalizability of findings to a broader spectrum of hotel selections [22]. In conclusion, acknowledging these limitations underscores the need for cautious interpretation and application of the study's outcomes, particularly beyond the specified parameters of one-star hotel choices within the staycation milieu.
2. RESEARCH METHODOLOGY
2.1 Simple Additive Weighting
This research employs the Simple Additive Weighting (SAW) method, comprising distinct stages: the determination of criteria and alternatives, the establishment of weights for criteria and alternatives, the creation of decision matrices and normalization, and the final stage of ranking based on the highest values [23]. The sequential breakdown outlines the crucial phases involved in the SAW methodology, from identifying criteria and alternatives to the conclusive ranking process [24]. This structured approach facilitates a comprehensive analysis and ensures transparency in the decision-making process [25]. In summation, the research methodology outlined herein provides a rigorous and methodical framework for evaluating and ranking alternatives within the context of the identified criteria.
Figure 1. The Implementation of Simple Additive Weighting (SAW) and Rank Order Centroid (ROC) Figure 1 shows the calculation process of SAW and ROC. The decision-making process involves distinct stages in selecting one-star hotels for staycation utilizing the Simple Additive Weighting (SAW) method in conjunction with the Rank Order Centroid (ROC) weighting [26]. Initially, criteria pertinent to staycation preferences encompassing facilities, services, rating, cleanliness, value for money, and location are delineated.
Subsequently, weights reflective of the relative significance of each criterion are assigned. The decision matrix is then constructed, wherein each one-star hotel is assessed against the identified criteria. Normalization is subsequently applied to standardize the scores, accounting for potential variations in measurement scales.
Weighted scores are computed by multiplying the normalized scores with their respective weights, thereby quantifying the contribution of each criterion to the decision [27]. Aggregating the weighted scores for each hotel facilitates determining the optimal staycation choice. Integrating SAW and ROC methodologies in this systematic process ensures a thorough and nuanced evaluation, culminating in the methodical ranking of one-star hotels to enhance the staycation experience.
The criteria employed in the computation process of the Simple Additive Weighting (SAW) method for evaluating alternatives consist of facilities, services, rating, value for money, and location. This fundamental assertion establishes the core dimensions considered during the assessment, encapsulating the essential factors contributing to the overall decision-making framework. Identifying specific criteria signifies a strategic selection tailored to the context under consideration, implying a deliberate focus on critical aspects in evaluating alternatives.
These chosen criteria collectively form a comprehensive set, addressing various facets pivotal in determining the optimal choice within the decision context. In conclusion, the specified criteria delineate the key parameters guiding the SAW computation process, reflecting a thoughtful and purposeful approach to decision-making within the scope of the identified dimensions.
In weighing the criteria values, the method employed is Rank Order Centroid. Acknowledging Rank Order Centroid as the chosen method signifies a deliberate decision-making approach, indicating a preference for a technique that emphasizes criteria ranking in determining their relative importance. Using the Rank Order Centroid suggests a strategic alignment with a method capable of capturing the ordinal relationships among criteria, thereby enhancing the precision of the weighting process. In conclusion, adopting the Rank Order Centroid underscores the methodological rigor employed in the criterion weighting phase, emphasizing its suitability for systematically establishing the significance of each criterion within the decision-making context.
Wm= 1
m∑ (1
i)
m1=1 (1)
Where is the result of Wm worth 1. In this study, the results of calculating the weight value based on the ROC method are as follows:
W1 = (1+
1
2+13+14+15+16 6 ) =2,45
6 = 0,4083 W2 = (0+
1
2+13+14+15+16 6 ) =1,45
6 = 0,2416 W3 = (0+0+
1 3+14+15+16
6 ) =0,95
6 = 0,1583 W4 = (0+0+0+
1 4+15+16 6 ) =0,61
6 = 0,1027 W5 = (0+0+0+0+
1 5+16 6 ) =0,36
6 = 0,0611 W6 = (0+0+0+0+0+
1 6 6 ) =0,16
6 = 0,0277
In light of the computations using Rank Order Centroid, it is discerned that the weights assigned to the criteria are as follows: W1 with a weight of 0.4083, w2 with a weight of 0.2416, w3 with a weight of 0.1583, w4 with a weight of 0.1027, w5 with a weight of 0.0611, and w6 with a weight of 0.0277. The essential information regarding the criterion weights is derived from the Rank Order Centroid method. The enumeration of specific weights illustrates the quantitative importance distribution among the criteria. The assigned weights reflect the relative significance of each criterion in the decision-making process, providing a nuanced perspective on their respective contributions. In conclusion, delineating these weights underscores the precision achieved through the Rank Order Centroid method, offering a clear and systematic representation of the criteria's hierarchical importance in the context of the decision-making framework.
Table 1. Construction of Decision Matrix
Criteria and Alternatives Facilities Services Rating Cleanliness
Value for Money
Location
Ghurfati Hotel Mangga Besar 8,5 8,8 8,5 8,8 8,9 8,7
Teduh Hostel Kota Tua 7,9 8,6 8,3 8,0 8,6 8,2
Konko Hostel 8,5 9,1 8,9 8,7 9,1 9,3
Urbanest Inn House TB
Simatupang 8,9 8,9 8,8 9,1 9,0 8,9
Criteria and Alternatives Facilities Services Rating Cleanliness
Value for Money
Location
Infiniti Hotel 8,1 8,5 8,2 8,3 8,4 8,7
Classification Benefit Benefit Benefit Cost Cost Cost
Table 1 is the culmination of the Identification of Criteria and Alternatives, Determination of Weights, and Construction of Decision Matrix. The decision matrix encapsulates vital components and stages of the decision- making process. The decision matrix becomes a pivotal visual representation, capturing the identified criteria and alternatives, the assigned weights reflecting their respective significance, and the decision matrix portraying the performance of each alternative across the specified criteria. The decision matrix is a foundational tool in the analytical framework, offering a condensed yet information-rich summary of the crucial steps undertaken in the decision-making process. In conclusion, Table 1 stands as a structured and visual synthesis of the multifaceted decision-making stages, facilitating a holistic understanding of the criteria and alternatives within the context of the study. A decision matrix is made, and normalization of the relative values is determined based on existing conditions in each thematic tourist destination as an alternative that will be processed according to the stages in the SAW method. Meanwhile, the equation used can be seen in Equation (2) and Equation (3) below.
Rij= { xij
Maxij} if j (benefit) (2)
Rij= {Minij
xij } if j (cost) (3)
Description :
Rij = Normalized performance rating
Maxij = Maximum value of each row and column Minij = Minimum Value of each row and column xij = Rows from matrix columns
With Rij is a performance rating normalized from alternative Ai on the attribute Cj ; i = 1, 2..,n dan j = 1, 2..,n hence the preference value for each alternative (Vi) will be calculated using the following equation (3).
Vi= ∑ni=0WJrij (4)
Description :
Vi = The final value of the alternative WJ = Predefined weight
rij = matrix normalization
At the ranking stage based on the most significant value, Vi value, which is larger than one, indicates that the alternative Ai be the chosen alternative or must be prioritized. By utilizing the SAW and ROC methodologies, a comprehensive process unfolds, encompassing normalization and ranking, to glean insights into identifying the most suitable one-star hotel for a staycation. The holistic nature of the methodological approach highlights the systematic application of SAW and ROC in the decision-making process. Recognizing normalization and ranking as integral steps emphasizes the precision of standardizing criterion scores and determining the optimal choice [28]. The integration of SAW and ROC signifies a systematic and nuanced strategy, facilitating a comprehensive assessment of one-star hotels tailored for staycation experiences. In conclusion, this combined methodological framework ensures a thorough analysis, enabling stakeholders to make well-informed decisions when selecting the most fitting one-star hotel for an enriched staycation experience.
3. RESULT AND DISCUSSION
Staycation, a consumer behavior within the hotel industry, involves using accommodation services during weekends for recreational purposes or to unwind. The primary focus is staycation as a discernible consumer pattern within the hospitality sector [29]—the temporal dimension of the behavior, emphasizing the specific usage of accommodation services over weekends. A staycation is a deliberate and leisure-oriented choice, reflecting a conscious decision to engage in recreational activities or seek relaxation within the confines of a hotel setting [30].
In conclusion, the characterization of staycation as a distinct consumer behavior highlights its significance in catering to the evolving preferences of individuals seeking brief respites and recreational indulgences within the context of accommodation services.
The surge in the staycation trend has heightened the interest in hotel visits or the intention to stay overnight, particularly with a focus on affordable pricing, thereby positioning one-star hotels as a suitable choice. The specific appeal of affordable pricing as a critical factor driving the heightened interest in hotel accommodations [31]. One- star hotels are posited as an appropriate and judicious choice, aligning with the preferences of individuals seeking
cost-effective options for their staycation experiences [32]. In conclusion, the burgeoning staycation trend not only amplifies the desire for hotel stays but also underscores the pertinence of one-star hotels in meeting the demands of a consumer base inclined towards budget-friendly yet fulfilling lodging experiences.
The results obtained from implementing the Simple Additive Weighting (SAW) and Rank Order Centroid (ROC) methods elucidate that the criteria instrumental in ranking the best one-star hotels for staycation encompass facilities, services, rating, value for money, and location. The key findings derived from applying the SAW and ROC methodologies, emphasizing their role in discerning the pivotal criteria for ranking one-star hotels. The dimensions identified as crucial factors determining optimal staycation choices include facilities, services, rating, value for money, and location. These criteria are considered essential, reflecting their significant impact on the staycation experience. In conclusion, using SAW and ROC methods not only aids in the identification but also underscores the importance of these criteria in the systematic ranking of the best one-star hotels, offering valuable insights for stakeholders and consumers alike.
Table 2. Normalization of Scores
Normalization W1 W2 W3 W4 W5 W6
R
0,95505618 0,96703297 0,95505618 0,90909091 0,94382022 0,942528736
0,88764045 0,94505495 0,93258427 1 0,97674419 1
0,95505618 1 1 0,91954023 0,92307692 0,88172043
1 0,97802198 0,98876404 0,87912088 0,93333333 0,921348315 0,91011236 0,93406593 0,92134831 0,96385542 1 0,942528736
Weight 0,41 0,24 0,16 0,10 0,06 0,03
Table 2 presents the outcomes resulting from the normalization process of the relative scores for each alternative by the weight values acquired through the Rank Order Centroid (ROC) method. Table 2 highlights its importance in displaying the normalized scores that portray the relative performance of each alternative against the established criteria. The explanation emphasizes the precision in normalizing the scores to align with the respective weights obtained from the ROC method. The normalization of scores is a crucial intermediate stage, offering a standardized representation of alternative performance that facilitates an impartial and equitable comparison. In conclusion, the creation of Table 2 holds significance as it provides a structured and normalized perspective on alternative scores, contributing to the fairness and objectivity of the decision-making process in the context of selecting one-star hotels for staycation.
Derived from the normalization results, the subsequent stages involve the computation of preference values for calculating weighted scores, aggregation of weighted scores, and ranking alternatives. The sequence of steps from the normalization process highlights their integral roles in the decision-making framework. The significance of computing preference values emphasizes their importance in the subsequent processes of aggregating weighted scores and ranking alternatives. These stages contribute to a systematic and informed decision-making process, allowing for a comprehensive evaluation and ranking of alternatives based on their respective performance against established criteria. In conclusion, successfully executing these sequential steps, initiated by the normalization process, ensures a robust analytical framework for discerning optimal alternatives when selecting one-star hotels for a staycation.
Table 3. Aggregation of Weighted Scores and Ranking of Alternatives
Preference Value (V) Total Rank
A1 0,38994944 0,23363516 0,15118539 0,09336364 0,05766742 0,026108046 0,95191 3 A2 0,3624236 0,22832527 0,14762809 0,1027 0,05967907 0,0277 0,92846 5 A3 0,38994944 0,2416 0,1583 0,09443678 0,0564 0,024423656 0,96511 2 A4 0,4083 0,23629011 0,15652135 0,09028571 0,05702667 0,025521348 0,97395 1 A5 0,37159888 0,22567033 0,14584944 0,09898795 0,0611 0,026108046 0,92931 4 Table 3 serves as the Aggregation of Weighted Scores and Ranking of Alternatives, delineating that A4 attains the first rank with a value of 0.97395, followed by A3, securing the second rank with a value of 0.96511, and A1 acquiring the third rank with a value of 0.95191. The enumeration of specific rankings and their corresponding values illustrates the hierarchical positioning of alternatives based on their comprehensive performance. The tabulated results indicate the optimal alternative (A4) and offer valuable insights into the nuanced differentials among the top-ranked alternatives. In conclusion, the meticulous presentation in Table 3 substantiates the effectiveness of the decision-making process, aiding stakeholders in identifying and selecting the most favorable one-star hotel for a satisfying staycation experience.
The outcomes of this study illuminate that opting for staycations in one-star hotels emerges as the optimal choice, particularly when considering factors such as facilities, services, rating, reasonable pricing, and strategic location [33]. The prominence of these criteria in influencing the staycation choice underscores the importance of a comprehensive evaluation framework, emphasizing the holistic nature of factors that contribute to a fulfilling staycation experience in one-star hotels [34]. In essence, the findings affirm the significance of a balanced
consideration of facilities, services, rating, affordability, and location when making choices related to staycations in one-star hotels, offering valuable insights for both consumers and industry stakeholders seeking to enhance the quality of staycation offerings in this specific hotel category [35]. The following is a simple dashboard design after the data scraping process from a one-star hotel that occupies the first position with a value weight of 0.97395.
Figure 2. Simple Dashboard of Urbanest Inn House TB Reviews
Figure 2 shows the simple dashboard design from the Oracle-apex application to visualize the data of the Urbanest Inn House TB reviewers in the Agoda application. Based on the findings from the reviews of Urbanest Inn House TB, it is discernible that most guests primarily originate from Indonesia, predominantly comprising couples or solo travelers. The most frequently utilized room types include deluxe double, deluxe twin room, and standard double, with stays typically lasting for one to two nights. These insights shed light on the hotel's guest demographics and preferences, offering valuable information for the establishment to tailor its services and accommodations to meet its clientele's prevalent needs and expectations. Such data is instrumental for hotel management in refining their marketing strategies and optimizing the overall guest experience, thereby enhancing the competitiveness and appeal of Urbanest Inn House TB in the hospitality industry.
The research findings indicate that each guest exhibits preferences concerning facilities, services, rating, affordability, and location for their staycation experiences. In the context of one-star hotels in the Jakarta area, numerous establishments offer diverse products and services; however, concerning the reviewer ratings on the Agoda application, Urbanest Inn House TB attains the top-ranking position, positioning itself as the foremost recommendation for a one-star hotel suitable for staycation activities. These outcomes underscore the discernment of guests in prioritizing specific criteria and highlight the distinct competitive advantage of Urbanest Inn House TB in meeting the expectations and preferences of staycations within the one-star hotel category in Jakarta.
However, it is crucial to note that this study is highly contextual. Variations in criteria, weights, and alternatives can yield divergent recommendations. Therefore, a more in-depth investigation with specific contexts is imperative to generate precise recommendations for further research development. This acknowledgment underscores the need for a nuanced and targeted examination that considers specific contextual factors, ensuring the relevance and accuracy of recommendations for subsequent research endeavors. The intricacies involved in decision-making necessitate a tailored approach to accommodate the contextual nuances, fostering a more robust foundation for future investigations in this domain.
4. CONCLUSION
This research's findings reveal that applying the Simple Additive Weighting (SAW) and Rank Order Centroid (ROC) methodologies in selecting a suitable one-star hotel for staycation activities in Jakarta recommends A4 as the premier choice with a weighted score of 0.97395. Subsequently, A3 secures the second rank with a score of 0.96511, and A1 acquires the third with a value of 0.95191. In addition, the ROC shows the weight of each
criterion: facilities (w1) with a weight of 0.4083, services (w2) with a weight of 0.2416, cleanliness (w3) with a weight of 0.1583, rating (w4) with a weight of 0.1027, value for money (w5) with a weight of 0.0611, and location (w6) with a weight of 0.0277. These results underscore the effectiveness of SAW and ROC methods in systematically evaluating and ranking alternatives based on established criteria, providing valuable insights for individuals seeking optimal staycation experiences in Jakarta's one-star hotels.
ACKNOWLEDGMENT
I sincerely thank Lembaga Penelitian dan Pengabdian Masyarakat (Institute for Research and Community Service), Faculty of Business Administration and Communication, Tourism Department, Atma Jaya Catholic University of Indonesia. The institution's unwavering support, guidance, and resources have been instrumental in completing my research endeavors. The collaborative and nurturing environment fostered by the faculty and staff has significantly contributed to the depth and quality of my academic pursuits. I extend my heartfelt thanks to all institution members for their dedication to fostering a conducive research atmosphere. This acknowledgment is a testament to the invaluable role played by Lembaga Penelitian dan Pengabdian Masyarakat in shaping my academic journey and enhancing my scholarly pursuits within the field of tourism.
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