ANALYTIC HIERARCHY PROCESS METHOD [AHP] |CO-WORKING MODEL
Analytic Hierarchy Process Method The AHP was developed and introduced by Saaty. This method has a comprehensive decision-making process with a hierarchical structure that consists of levels and links. The AHP’s characteristics are suitable for handling multiple levels and criteria. In order to use AHP, scholars have to identify several qualitative and quantitative criteria. This will be helpful to evaluate the priorities among multiple alternatives. The strong point of this method is that it is appropriate to transform qualitative information into quantitative information. It is based on a person’s perceptions identified through a survey.
Saaty mentioned that “The AHP is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales”. The AHP generally uses a nine-point scale and provides a consistency ratio with relative priority within criteria, elements, and alternatives. The nine-point scale is subdivided into equally, moderately, strongly, very strongly, and absolutely preferred (with the values of 1, 3, 5, 7, and 9, respectively), as well as intermediate values (2, 4, 6, and 8) . The AHP has been widely applied to evaluate complex and comprehensive impacts during the last few decades.
Economic analysis, forecasting, and strategic planning are performed by using AHP. Furthermore, in various industries, AHP has been applied for resource allocation, performance evaluation, business decision making, and priority rating . Some papers apply the AHP approach in the fields of entrepreneurship and innovation success factors, innovative capabilities and the intellectual property of firms, and important factors of innovation clusters. Liu and Chin used this method to propose an intellectual property management excellence audit system, and to identify its critical success factors . Chen and Wang revealed the critical operational factors of success for the information service industry using the AHP approach . Sun et al. attempted to understand the driving forces of the innovation cluster by analyzing priorities from the Hsinchu Science Park in Taiwan using the fuzzy AHP method . Nevertheless, no coworking space research has been conducted using AHP, and only Seo et al. focused on the providers’ perspective.
In order to capture the competitiveness of coworking spaces, both providers and users’ perspectives need to be understood together. If the users and providers’ specific needs are grasped, coworking spaces can achieve sustainable design and become a source of entrepreneurial sustainability. Few scholars have tried to understand both sides’ priorities. Kher et al. proposed a network selection model with two ranking schemes that indicate the providers and users’ specific needs.
This research emphasized the importance of understanding both sides’ ranking results in a network industry. Da Cruz et al. tried to measure the users and providers’ priorities using AHP in a seaport industry. They examined important factors of Iberian seaport competitiveness based on the related stakeholders—that is, liner shipping companies (users) and seaport service providers. They identified seaport facilities and equipment, channel depth, vessel turnaround time, and proximity to import/export area as key factors. Based on the results, the users and providers’ priorities regarding key factors were found to be totally different. Vessel turnaround time was the most important factor from the users’ view, while seaport facilities and equipment were the best factors in the providers’ view.
The AHP is designed to decompose a complex, multi-criteria problem into multiple levels of hierarchy with the top level as the goal or objective, the intermediate levels as the categories and criteria, and the lowest level as the alternatives . It is a subjective methodology that requires experts in the particular fields to act as evaluators who provide their expert knowledge. Decision makers need to decide the priorities by conducting pairwise comparisons between complex criteria.
The AHP method can support a reasonable approximation when the policy and decision maker’s judgments are applied.
We propose to analyze the important factors of success for co-working space operation through the AHP approach by considering both hosts and users’ perspectives. Following previous studies, we performed comparative analysis using the AHP method for co-working space operation. The results will reveal discrepancies between the users and providers, and suggest ways for co-working spaces to obtain a competitive edge for sustainable operation.
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